Instructions to use deepset/xlm-roberta-large-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/xlm-roberta-large-squad2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="deepset/xlm-roberta-large-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/xlm-roberta-large-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/xlm-roberta-large-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#5)
Mayank Jobanputra +1: SFconvertbot - Adding `safetensors` variant of this model (7d2eebf9a0858a7b622006ef9ab4d956aba25bb2) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>82faf62
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Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#4)
Sebastian +1: autoevaluator - Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (a65041a008a2a69fd77546902b845cd3fbc55c11) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>4c0f212
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Add evaluation results on the squad_v2 config of squad_v2 (#1)
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