Instructions to use cliang1453/deberta-v3-base-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cliang1453/deberta-v3-base-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="cliang1453/deberta-v3-base-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("cliang1453/deberta-v3-base-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("cliang1453/deberta-v3-base-squadv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50ede92b34c491fbc465eb15720dd3d507334baf687122c4484972528730caea
- Size of remote file:
- 735 MB
- SHA256:
- c92965d64cec68ca290f8991098a83cc66c7e5eab0981475219b5589bcdd373a
路
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