Instructions to use CambridgeMolecularEngineering/bert-base-cased-scsmall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CambridgeMolecularEngineering/bert-base-cased-scsmall with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CambridgeMolecularEngineering/bert-base-cased-scsmall")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scsmall") model = AutoModelForMaskedLM.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scsmall", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:552559a27319e7f0a88d45ef3a7c9dcaecebd3f7dc618747f6f955879fe2c4ba
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size 433391224
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