Instructions to use facebook/xmod-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/xmod-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="facebook/xmod-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/xmod-base") model = AutoModelForMaskedLM.from_pretrained("facebook/xmod-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Add XLM-R tokenizer files (#2)
- Copy XLM-R tokenizer to this repo (007e82656cdb52dda51a3f6b674aa57df98ba058) Co-authored-by: Jannis Vamvas <jvamvas@users.noreply.huggingface.co>1ff2383
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Remove "classifier_dropout": null
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Update README.md
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XMOD -> Xmod
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Add lang_id column to table of languages
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Add model card
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Add metadata
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Upload model
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initial commit
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