Instructions to use FacebookAI/xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-roberta-base") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Add TF weights
Joao GanteValidated by the `pt_to_tf` CLI. Max crossload hidden state difference=8.106e-06; Max converted hidden state difference=8.106e-06.9e83a6a
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Migrate model card from transformers-repo
Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/xlm-roberta-base-README.mdd9d8a8e
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initial commit
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