Question Answering
Transformers
PyTorch
Safetensors
English
deberta-v2
deberta
deberta-v3
deberta-v3-large
Eval Results (legacy)
Instructions to use deepset/deberta-v3-large-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/deberta-v3-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/deberta-v3-large-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/deberta-v3-large-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/deberta-v3-large-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Update README.md
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Add evaluation results on the squad_v2 config of squad_v2 (#1)
- Add evaluation results on the squad_v2 config of squad_v2 (c8b7584fd31df58d9e4ead7bd17cfe15c8608dee) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>f030715 -
Update README.md
a02020b -
Create README.md
de73c83 -
Add new model to Hugging Face.
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initial commit
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