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transformers
# bert-base-en-hi-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-hi-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-hi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-hi-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-hi-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-it-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-it-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-it-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-it-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-it-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-it-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-it-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-it-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-ja-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-ja-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-ja-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-ja-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-ja-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-ja-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-ja-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-ja-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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transformers
# bert-base-en-lt-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-lt-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-lt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-lt-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-lt-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-lt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-lt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-lt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-nl-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-nl-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-nl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-nl-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-nl-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-nl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-nl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 64, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-nl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-no-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-no-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-no-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-no-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-no-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-no-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-no-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-no-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
transformers
# bert-base-en-pl-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-pl-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-pl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-pl-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-pl-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-pl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-pl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 64, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-pl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-pt-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-pt-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-pt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": ["multilingual", "en", "pt"], "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-pt-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "multilingual", "en", "pt", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual", "en", "pt" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #en #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-pt-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-pt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #en #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-pt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 68, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #en #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-pt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-ro-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-ro-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-ro-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-ro-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-ro-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-ro-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-ro-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-ro-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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transformers
# bert-base-en-ru-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-ru-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-ru-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-ru-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-ru-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-ru-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-ru-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 64, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-ru-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-sw-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-sw-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-sw-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-sw-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-sw-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-sw-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-sw-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 104, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-sw-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-th-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-th-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-th-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-th-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-th-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-th-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-th-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 64, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-th-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-tr-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-tr-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-tr-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-tr-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-tr-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-tr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-tr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-tr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-uk-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-uk-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-uk-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-uk-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-uk-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-uk-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-uk-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-uk-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-ur-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-ur-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-ur-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-ur-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-ur-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-ur-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-ur-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-ur-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-vi-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-vi-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-vi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-vi-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-vi-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-vi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-vi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-vi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-zh-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-zh-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-zh-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": ["multilingual", "en", "zh"], "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}]}
fill-mask
Geotrend/bert-base-en-zh-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "multilingual", "en", "zh", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual", "en", "zh" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #en #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-zh-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-zh-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #en #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-zh-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 68, 103, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #multilingual #en #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-zh-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-en-zh-hi-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-zh-hi-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-en-zh-hi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-en-zh-hi-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-en-zh-hi-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-en-zh-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-en-zh-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 59, 105, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-en-zh-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-es-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-es-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-es-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "es", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-es-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "es", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "es" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-es-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-es-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-es-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 62, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-es-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-fr-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-fr-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-fr-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "fr", "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Paris est la [MASK] de la France."}, {"text": "Paris est la capitale de la [MASK]."}, {"text": "L'\u00e9lection am\u00e9ricaine a eu [MASK] en novembre 2020."}]}
fill-mask
Geotrend/bert-base-fr-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "fr", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "fr" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-fr-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-fr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-fr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 62, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-fr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-hi-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-hi-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-hi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "hi", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-hi-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "hi", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "hi" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #hi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-hi-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #hi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #hi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-hi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-it-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-it-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-it-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "it", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-it-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "it", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "it" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-it-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-it-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-it-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-it-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-ja-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-ja-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-ja-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ja", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-ja-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "ja", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ja" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-ja-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-ja-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-ja-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 62, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-ja-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-lt-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-lt-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-lt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "lt", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-lt-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "lt", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "lt" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #lt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-lt-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-lt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #lt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-lt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #lt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-lt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-nl-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-nl-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-nl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "nl", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-nl-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "nl", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "nl" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #nl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-nl-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-nl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #nl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-nl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #nl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-nl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-no-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-no-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-no-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": false, "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-no-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "no", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "no" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #no #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-no-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-no-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #no #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-no-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #no #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-no-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-pl-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-pl-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-pl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "pl", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-pl-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "pl", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "pl" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #pl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-pl-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-pl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #pl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-pl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #pl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-pl-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-pt-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-pt-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-pt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "pt", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-pt-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "pt", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "pt" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-pt-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-pt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-pt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-pt-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-ro-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-ro-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-ro-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ro", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-ro-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "ro", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ro" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #ro #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-ro-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-ro-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #ro #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-ro-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #ro #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-ro-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-ru-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-ru-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-ru-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ru", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-ru-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "ru", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "has_space", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ru" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ru #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
# bert-base-ru-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-ru-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ru #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n", "# bert-base-ru-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 66, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ru #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n# bert-base-ru-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-sw-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-sw-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-sw-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "sw", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-sw-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "sw", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "sw" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-sw-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-sw-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-sw-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 102, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-sw-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-th-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-th-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-th-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "th", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-th-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "th", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "th" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #th #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-th-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-th-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #th #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-th-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #th #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-th-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-tr-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-tr-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-tr-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "tr", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-tr-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "tr", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "tr" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #tr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-tr-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-tr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #tr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-tr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 62, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #tr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-tr-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-uk-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-uk-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-uk-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "uk", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-uk-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "uk", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "uk" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #uk #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-uk-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-uk-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #uk #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-uk-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 62, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #uk #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-uk-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-ur-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-ur-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-ur-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ur", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-ur-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "ur", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ur" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ur #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-ur-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-ur-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ur #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-ur-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 62, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #ur #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-ur-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-vi-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-vi-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-vi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "vi", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-vi-cased
[ "transformers", "pytorch", "tf", "jax", "bert", "fill-mask", "vi", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "vi" ]
TAGS #transformers #pytorch #tf #jax #bert #fill-mask #vi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-vi-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-vi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #vi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-vi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 57, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #bert #fill-mask #vi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-vi-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# bert-base-zh-cased We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages. Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-zh-cased") model = AutoModel.from_pretrained("Geotrend/bert-base-zh-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "zh", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/bert-base-zh-cased
[ "transformers", "pytorch", "tf", "jax", "safetensors", "bert", "fill-mask", "zh", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "zh" ]
TAGS #transformers #pytorch #tf #jax #safetensors #bert #fill-mask #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# bert-base-zh-cased We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# bert-base-zh-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# bert-base-zh-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 62, 101, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# bert-base-zh-cased\n\nWe are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages.\n\nUnlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
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transformers
# distilbert-base-25lang-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. Handled languages: en, fr, es, de, zh, ar, ru, vi, el, bg, th, tr, hi, ur, sw, nl, uk, ro, pt, it, lt, no, pl, da and ja. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-25lang-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-25lang-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermbert, title={Load What You Need: Smaller Versions of Multilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": ["multilingual", "en", "fr", "es", "de", "zh", "ar", "ru", "vi", "el", "bg", "th", "tr", "hi", "ur", "sw", "nl", "uk", "ro", "pt", "it", "lt", false, "pl", "da", "ja"], "license": "apache-2.0", "datasets": "wikipedia", "widget": [{"text": "Google generated 46 billion [MASK] in revenue."}, {"text": "Paris is the capital of [MASK]."}, {"text": "Algiers is the largest city in [MASK]."}, {"text": "Paris est la [MASK] de la France."}, {"text": "Paris est la capitale de la [MASK]."}, {"text": "L'\u00e9lection am\u00e9ricaine a eu [MASK] en novembre 2020."}, {"text": "\u062a\u0642\u0639 \u0633\u0648\u064a\u0633\u0631\u0627 \u0641\u064a [MASK] \u0623\u0648\u0631\u0648\u0628\u0627"}, {"text": "\u0625\u0633\u0645\u064a \u0645\u062d\u0645\u062f \u0648\u0623\u0633\u0643\u0646 \u0641\u064a [MASK]."}]}
fill-mask
Geotrend/distilbert-base-25lang-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "en", "fr", "es", "de", "zh", "ar", "ru", "vi", "el", "bg", "th", "tr", "hi", "ur", "sw", "nl", "uk", "ro", "pt", "it", "lt", "no", "pl", "da", "ja", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual", "en", "fr", "es", "de", "zh", "ar", "ru", "vi", "el", "bg", "th", "tr", "hi", "ur", "sw", "nl", "uk", "ro", "pt", "it", "lt", "no", "pl", "da", "ja" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #fr #es #de #zh #ar #ru #vi #el #bg #th #tr #hi #ur #sw #nl #uk #ro #pt #it #lt #no #pl #da #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-25lang-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. Handled languages: en, fr, es, de, zh, ar, ru, vi, el, bg, th, tr, hi, ur, sw, nl, uk, ro, pt, it, lt, no, pl, da and ja. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-25lang-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nHandled languages: en, fr, es, de, zh, ar, ru, vi, el, bg, th, tr, hi, ur, sw, nl, uk, ro, pt, it, lt, no, pl, da and ja.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #fr #es #de #zh #ar #ru #vi #el #bg #th #tr #hi #ur #sw #nl #uk #ro #pt #it #lt #no #pl #da #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-25lang-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nHandled languages: en, fr, es, de, zh, ar, ru, vi, el, bg, th, tr, hi, ur, sw, nl, uk, ro, pt, it, lt, no, pl, da and ja.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 111, 148, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #fr #es #de #zh #ar #ru #vi #el #bg #th #tr #hi #ur #sw #nl #uk #ro #pt #it #lt #no #pl #da #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-25lang-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\nHandled languages: en, fr, es, de, zh, ar, ru, vi, el, bg, th, tr, hi, ur, sw, nl, uk, ro, pt, it, lt, no, pl, da and ja.\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-ar-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ar-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-ar-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ar", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-ar-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "ar", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ar" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #ar #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-ar-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #ar #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #ar #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-bg-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-bg-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-bg-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "bg", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-bg-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "bg", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "bg" ]
TAGS #transformers #pytorch #distilbert #fill-mask #bg #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-bg-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-bg-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #bg #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-bg-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #bg #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-bg-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-da-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-da-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-da-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "da", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-da-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "da", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "da" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #da #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-da-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #da #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #da #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-de-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-de-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-de-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "de", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-de-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "de", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "de" ]
TAGS #transformers #pytorch #distilbert #fill-mask #de #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-de-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #de #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #de #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-el-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-el-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-el-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "el", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-el-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "el", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "el" ]
TAGS #transformers #pytorch #distilbert #fill-mask #el #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-el-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-el-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #el #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-el-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #el #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-el-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-ar-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-ar-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-ar-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-ar-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-ar-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-bg-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-bg-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-bg-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-bg-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-bg-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-bg-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-bg-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-bg-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "en", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "en", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "en" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #en #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #en #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #en #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-da-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-da-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-da-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-da-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-da-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-de-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-de-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-de-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-de-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-de-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-el-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-el-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-el-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-el-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-el-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-el-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-el-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-el-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-el-ru-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-el-ru-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-el-ru-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-el-ru-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-el-ru-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-el-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-el-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-el-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-es-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-es-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-es-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-es-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-es-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-es-it-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-es-it-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-es-it-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-es-it-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-es-it-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-es-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-es-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-es-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-es-pt-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-es-pt-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-es-pt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-es-pt-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-es-pt-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-es-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-es-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-es-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-es-zh-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-es-zh-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-es-zh-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": ["multilingual", "en", "es", "zh"], "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-es-zh-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "en", "es", "zh", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual", "en", "es", "zh" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #es #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-es-zh-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-es-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #es #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-es-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 66, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #es #zh #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-es-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-ar-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-ar-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-ar-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-ar-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-ar-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": ["multilingual", "en", "fr"], "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "en", "fr", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual", "en", "fr" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 64, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-da-ja-vi-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-da-ja-vi-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-da-ja-vi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-da-ja-vi-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-da-ja-vi-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-da-ja-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-da-ja-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-da-ja-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-de-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-de-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-de-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-de-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-de-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-de-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-de-no-da-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-de-no-da-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-de-no-da-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-de-no-da-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-de-no-da-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-de-no-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-de-no-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-de-no-da-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-es-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-es-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-es-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-es-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-es-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-es-de-zh-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-es-de-zh-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-es-de-zh-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-es-de-zh-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-es-de-zh-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-es-de-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-es-de-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-es-de-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-es-pt-it-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-es-pt-it-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-es-pt-it-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": ["multilingual", "en", "fr", "es", "pt", "it"], "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-es-pt-it-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "en", "fr", "es", "pt", "it", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual", "en", "fr", "es", "pt", "it" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #en #fr #es #pt #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-es-pt-it-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-es-pt-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #en #fr #es #pt #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-es-pt-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 65, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #en #fr #es #pt #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-es-pt-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-it-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-it-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-it-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-it-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-it-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-lt-no-pl-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-lt-no-pl-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-lt-no-pl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-lt-no-pl-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-lt-no-pl-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-lt-no-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-lt-no-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-lt-no-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-nl-ru-ar-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-nl-ru-ar-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-nl-ru-ar-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-nl-ru-ar-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-nl-ru-ar-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-nl-ru-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-nl-ru-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-nl-ru-ar-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-uk-el-ro-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-uk-el-ro-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-uk-el-ro-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-uk-el-ro-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-uk-el-ro-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-uk-el-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-uk-el-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-uk-el-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-zh-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-zh-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-zh-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-zh-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-zh-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-fr-zh-ja-vi-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-zh-ja-vi-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-zh-ja-vi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-fr-zh-ja-vi-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-fr-zh-ja-vi-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-fr-zh-ja-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-fr-zh-ja-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 96, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-fr-zh-ja-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-hi-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-hi-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-hi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-hi-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-hi-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-it-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-it-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-it-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-it-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-it-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-ja-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-ja-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-ja-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-ja-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-ja-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-ja-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-ja-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-ja-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-lt-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-lt-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-lt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-lt-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-lt-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-lt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-lt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-lt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-nl-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-nl-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-nl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-nl-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-nl-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-nl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-nl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-nl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-no-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-no-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-no-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-no-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-no-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-no-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-no-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-no-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-pl-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-pl-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-pl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-pl-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-pl-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-pt-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-pt-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-pt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-pt-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-pt-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-ro-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-ro-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-ro-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-ro-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-ro-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-ru-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-ru-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-ru-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-ru-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-ru-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-sw-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-sw-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-sw-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": ["multilingual", "en", "sw"], "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-sw-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "en", "sw", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual", "en", "sw" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-sw-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-sw-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-sw-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 65, 91, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #en #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-sw-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-th-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-th-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-th-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-th-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-th-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-th-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-th-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-th-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-tr-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-tr-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-tr-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-tr-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-tr-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-tr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-tr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 60, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-tr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-uk-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-uk-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-uk-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-uk-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-uk-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-uk-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-uk-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-uk-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-ur-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-ur-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-ur-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-ur-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-ur-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-ur-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-ur-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-ur-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-vi-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-vi-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-vi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-vi-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-vi-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-vi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-zh-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-zh-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-zh-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-zh-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-zh-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 90, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-zh-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-en-zh-hi-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-zh-hi-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-zh-hi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "multilingual", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-en-zh-hi-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "multilingual", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "multilingual" ]
TAGS #transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-en-zh-hi-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-en-zh-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-en-zh-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 55, 92, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #multilingual #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-en-zh-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-es-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-es-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-es-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "es", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-es-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "es", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "es" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-es-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-es-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-fr-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-fr-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-fr-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "fr", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-fr-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "fr", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "fr" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-fr-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-fr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-fr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #fr #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-fr-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-hi-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-hi-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-hi-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "hi", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-hi-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "hi", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "hi" ]
TAGS #transformers #pytorch #distilbert #fill-mask #hi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-hi-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #hi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #hi #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-hi-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-it-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-it-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-it-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "it", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-it-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "it", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "it" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-it-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #it #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-it-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-ja-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ja-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-ja-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ja", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-ja-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "ja", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ja" ]
TAGS #transformers #pytorch #distilbert #fill-mask #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-ja-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-ja-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-ja-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #ja #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-ja-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-lt-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-lt-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-lt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "lt", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-lt-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "lt", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "lt" ]
TAGS #transformers #pytorch #distilbert #fill-mask #lt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-lt-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-lt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #lt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-lt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #lt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-lt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-nl-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-nl-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-nl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "nl", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-nl-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "nl", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "nl" ]
TAGS #transformers #pytorch #distilbert #fill-mask #nl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-nl-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-nl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #nl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-nl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #nl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-nl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-no-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-no-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-no-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": false, "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-no-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "no", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "no" ]
TAGS #transformers #pytorch #distilbert #fill-mask #no #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-no-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-no-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #no #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-no-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #no #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-no-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-pl-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-pl-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-pl-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "pl", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-pl-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "pl", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "pl" ]
TAGS #transformers #pytorch #distilbert #fill-mask #pl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-pl-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #pl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 53, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #pl #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-pl-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-pt-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-pt-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-pt-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "pt", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-pt-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "pt", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "pt" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-pt-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #pt #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-pt-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-ro-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ro-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-ro-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ro", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-ro-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "ro", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ro" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #ro #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-ro-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #ro #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #ro #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-ro-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-ru-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ru-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-ru-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "ru", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-ru-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "ru", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "ru" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #ru #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-ru-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #ru #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #ru #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-ru-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-sw-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-sw-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-sw-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "sw", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-sw-cased
[ "transformers", "pytorch", "distilbert", "fill-mask", "sw", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "sw" ]
TAGS #transformers #pytorch #distilbert #fill-mask #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-sw-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-sw-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #distilbert #fill-mask #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-sw-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 54, 89, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #distilbert #fill-mask #sw #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-sw-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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null
null
transformers
# distilbert-base-th-cased We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf). ## How to use ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-th-cased") model = AutoModel.from_pretrained("Geotrend/distilbert-base-th-cased") ``` To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers). ### How to cite ```bibtex @inproceedings{smallermdistilbert, title={Load What You Need: Smaller Versions of Mutlilingual BERT}, author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire}, booktitle={SustaiNLP / EMNLP}, year={2020} } ``` ## Contact Please contact [email protected] for any question, feedback or request.
{"language": "th", "license": "apache-2.0", "datasets": "wikipedia"}
fill-mask
Geotrend/distilbert-base-th-cased
[ "transformers", "pytorch", "safetensors", "distilbert", "fill-mask", "th", "dataset:wikipedia", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]
2022-03-02T23:29:04+00:00
[]
[ "th" ]
TAGS #transformers #pytorch #safetensors #distilbert #fill-mask #th #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
# distilbert-base-th-cased We are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages. Our versions give exactly the same representations produced by the original model which preserves the original accuracy. For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT. ## How to use To generate other smaller versions of multilingual transformers please visit our Github repo. ### How to cite ## Contact Please contact amine@URL for any question, feedback or request.
[ "# distilbert-base-th-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ "TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #th #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n", "# distilbert-base-th-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.", "## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.", "### How to cite", "## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
[ 58, 88, 24, 5, 16 ]
[ "passage: TAGS\n#transformers #pytorch #safetensors #distilbert #fill-mask #th #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# distilbert-base-th-cased\n\nWe are sharing smaller versions of distilbert-base-multilingual-cased that handle a custom number of languages.\n\nOur versions give exactly the same representations produced by the original model which preserves the original accuracy.\n\n\nFor more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.## How to use\n\n\n\nTo generate other smaller versions of multilingual transformers please visit our Github repo.### How to cite## Contact \n\nPlease contact amine@URL for any question, feedback or request." ]
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