Instructions to use FacebookAI/xlm-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-roberta-large") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-roberta-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download src/models/auto_models.py from FacebookAI/xlm-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 353 Bytes
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https://huggingface.co/FacebookAI/xlm-roberta-large/resolve/refs%2Fpr%2F8/src/models/auto_models.py
- Command line
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hf download hf://FacebookAI/xlm-roberta-large@refs/pr/8/src/models/auto_models.py
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curl -L -o auto_models.py https://huggingface.co/FacebookAI/xlm-roberta-large/resolve/refs%2Fpr%2F8/src/models/auto_models.py
353 Bytes
| from transformers import AutoModelForTokenClassification, AutoModelForQuestionAnswering | |
| from src.utils.mapper import configmapper | |
| configmapper.map("models", "autotoken")(AutoModelForTokenClassification) | |
| configmapper.map("models", "autotoken_3cls")(AutoModelForTokenClassification) | |
| configmapper.map("models", "autospans")(AutoModelForQuestionAnswering) | |