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:
- 34e3f84853a80e19ac30af341fbadfccb8677d34ceb98d06222895324192929f
- Size of remote file:
- 1.68 GB
- SHA256:
- b0d3ee531b8ad3f0073bd1ac3052a2d935c1f48ab2f525d5db393049acdba5fd
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