Instructions to use CambridgeMolecularEngineering/bert-base-cased-scmedium-scqa2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CambridgeMolecularEngineering/bert-base-cased-scmedium-scqa2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="CambridgeMolecularEngineering/bert-base-cased-scmedium-scqa2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scmedium-scqa2") model = AutoModelForQuestionAnswering.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scmedium-scqa2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b42d398adf03bb790429dd2253057f78d33458305b6f50239be85aff07150e33
- Size of remote file:
- 431 MB
- SHA256:
- 0935521a190f0e41e878cf3961293fbe50f83656d7d4d91ea61d6421568152b2
路
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