Question Answering
Transformers
PyTorch
Safetensors
English
deberta-v2
deberta
deberta-v3
Eval Results (legacy)
Instructions to use deepset/deberta-v3-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/deberta-v3-base-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-base-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/deberta-v3-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/deberta-v3-base-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/deberta-v3-base-squad2: direct link, hf CLI and curl.
- Browser
- Download file 735 MB
-
https://huggingface.co/deepset/deberta-v3-base-squad2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepset/deberta-v3-base-squad2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/deberta-v3-base-squad2/resolve/main/pytorch_model.bin
735 MB
- Xet hash:
- fb288b6eb1923427c246b8f03cb39e1da40c7e270f95d216d89dc0b740dc0a97
- Size of remote file:
- 735 MB
- SHA256:
- 8a247792955136c18184a22bacf7b317694d54b666897700179d8ccc56538b36
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