Instructions to use CambridgeMolecularEngineering/bert-base-cased-scmedium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CambridgeMolecularEngineering/bert-base-cased-scmedium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CambridgeMolecularEngineering/bert-base-cased-scmedium")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scmedium") model = AutoModelForMaskedLM.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scmedium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b516af53ee89e64b0c773bdcf3874fb3b3d17e0ea8ec5ae4faeb683487a0757
- Size of remote file:
- 433 MB
- SHA256:
- f7f3cb6aafff609746550fea8697e9b1cf3253314312bf9e6e3c7ec9d2093774
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