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@@ -24,41 +24,31 @@ You can use this model directly with a pipeline for masked language modeling:
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  Here is how to use this model to get the features of a given text in PyTorch:
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  ```python
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- from transformers import AutoTokenizer, AutoModelForMaskedLM
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- tokenizer = AutoTokenizer.from_pretrained('cis-lmu/glot500-base')
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- model = AutoModelForMaskedLM.from_pretrained("cis-lmu/glot500-base")
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- # prepare input
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- text = "Replace me by any text you'd like."
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- encoded_input = tokenizer(text, return_tensors='pt')
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- # forward pass
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- output = model(**encoded_input)
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  ```
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  ### BibTeX entry and citation info
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  ```bibtex
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  @inproceedings{imanigooghari-etal-2023-glot500,
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- title = "Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages",
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- author = {ImaniGooghari, Ayyoob and
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- Lin, Peiqin and
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- Kargaran, Amir Hossein and
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- Severini, Silvia and
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- Jalili Sabet, Masoud and
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- Kassner, Nora and
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- Ma, Chunlan and
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- Schmid, Helmut and
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- Martins, Andr{\'e} and
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- Yvon, Fran{\c{c}}ois and
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- Sch{\"u}tze, Hinrich},
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- booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
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- month = jul,
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- year = "2023",
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- address = "Toronto, Canada",
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- publisher = "Association for Computational Linguistics",
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- url = "https://aclanthology.org/2023.acl-long.61",
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- pages = "1082--1117",
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  }
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  ```
 
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  Here is how to use this model to get the features of a given text in PyTorch:
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  ```python
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+ >>> from transformers import AutoTokenizer, AutoModelForMaskedLM
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+ >>> tokenizer = AutoTokenizer.from_pretrained('cis-lmu/glot500-base')
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+ >>> model = AutoModelForMaskedLM.from_pretrained("cis-lmu/glot500-base")
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+ >>> # prepare input
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+ >>> text = "Replace me by any text you'd like."
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+ >>> encoded_input = tokenizer(text, return_tensors='pt')
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+ >>> # forward pass
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+ >>> output = model(**encoded_input)
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  ```
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  ### BibTeX entry and citation info
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  ```bibtex
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  @inproceedings{imanigooghari-etal-2023-glot500,
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+ title = {Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages},
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+ author = {ImaniGooghari, Ayyoob and Lin, Peiqin and Kargaran, Amir Hossein and Severini, Silvia and Jalili Sabet, Masoud and Kassner, Nora and Ma, Chunlan and Schmid, Helmut and Martins, Andr{\'e} and Yvon, Fran{\c{c}}ois and Sch{\"u}tze, Hinrich},
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+ year = 2023,
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+ month = jul,
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+ booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
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+ publisher = {Association for Computational Linguistics},
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+ address = {Toronto, Canada},
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+ pages = {1082--1117},
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+ url = {https://aclanthology.org/2023.acl-long.61}
 
 
 
 
 
 
 
 
 
 
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  }
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  ```