Instructions to use BrianS15/prot_bert-finetuned-CDR1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BrianS15/prot_bert-finetuned-CDR1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BrianS15/prot_bert-finetuned-CDR1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BrianS15/prot_bert-finetuned-CDR1") model = AutoModelForMaskedLM.from_pretrained("BrianS15/prot_bert-finetuned-CDR1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2024aa00c4f9a8dcde16ba9f772ae0d494126d6b83202e7ca6fccc0fd46133a
- Size of remote file:
- 3.96 kB
- SHA256:
- aff9082f110e5e912e6c2e057976416837a0262c473d26d88e92df408cd6e1d5
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