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
Download pytorch_model.bin from deepset/deberta-v3-large-squad2: direct link, hf CLI and curl.
- Browser
- Download file 1.74 GB
-
https://huggingface.co/deepset/deberta-v3-large-squad2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepset/deberta-v3-large-squad2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/deberta-v3-large-squad2/resolve/main/pytorch_model.bin
1.74 GB
- Xet hash:
- 7238ab6834006234247c3fb19d32628d98652acd626f26f6d7f11170bbe6a403
- Size of remote file:
- 1.74 GB
- SHA256:
- cc31220db2ad55672fea1f369664c17628c021b528b1ae65b4b3f2bc7c6910e4
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