Instructions to use CambridgeMolecularEngineering/opticalbert_cased-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CambridgeMolecularEngineering/opticalbert_cased-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="CambridgeMolecularEngineering/opticalbert_cased-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("CambridgeMolecularEngineering/opticalbert_cased-squad2") model = AutoModelForQuestionAnswering.from_pretrained("CambridgeMolecularEngineering/opticalbert_cased-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_null_odds.json from CambridgeMolecularEngineering/opticalbert_cased-squad2: direct link, hf CLI and curl.
- Browser
- Download file 618 kB
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https://huggingface.co/CambridgeMolecularEngineering/opticalbert_cased-squad2/resolve/main/eval_null_odds.json
- Command line
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hf download hf://CambridgeMolecularEngineering/opticalbert_cased-squad2/eval_null_odds.json
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curl -L -o eval_null_odds.json https://huggingface.co/CambridgeMolecularEngineering/opticalbert_cased-squad2/resolve/main/eval_null_odds.json
618 kB
File too large to display, you can check the raw version instead.