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README.md
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third party and subject to a separate license, available
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[here](https://github.com/facebookresearch/fairseq).
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__Arguments__
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third party and subject to a separate license, available
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[here](https://github.com/facebookresearch/fairseq).
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## Links
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* [XLM-RoBERTa Quickstart Notebook](https://www.kaggle.com/code/laxmareddypatlolla/xlm-roberta-quickstart-notebook)
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* [XLM-RoBERTa API Documentation](https://keras.io/keras_hub/api/models/xlm_roberta/)
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* [XLM-RoBERTa Model Card](https://huggingface.co/FacebookAI/xlm-roberta-base)
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* [KerasHub Beginner Guide](https://keras.io/guides/keras_hub/getting_started/)
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* [KerasHub Model Publishing Guide](https://keras.io/guides/keras_hub/upload/)
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## Installation
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Keras and KerasHub can be installed with:
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```
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pip install -U -q keras-hub
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pip install -U -q keras
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```
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Jax, TensorFlow, and Torch come preinstalled in Kaggle Notebooks. For instructions on installing them in another environment see the [Keras Getting Started](https://keras.io/getting_started/) page.
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## Presets
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The following model checkpoints are provided by the Keras team. Full code examples for each are available below.
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| Preset name | Parameters | Description |
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|----------------|------------|--------------------------------------------------|
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| xlm_roberta_base_multi | 277.45M | 12-layer XLM-RoBERTa model where case is maintained. Trained on CommonCrawl in 100 languages.|
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| xlm_roberta_large_multi | 558.84M | 24-layer XLM-RoBERTa model where case is maintained. Trained on CommonCrawl in 100 languages. |
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__Arguments__
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