Instructions to use virtual-human-chc/prot_bert_bfd_ss3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use virtual-human-chc/prot_bert_bfd_ss3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="virtual-human-chc/prot_bert_bfd_ss3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("virtual-human-chc/prot_bert_bfd_ss3") model = AutoModelForTokenClassification.from_pretrained("virtual-human-chc/prot_bert_bfd_ss3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fe1489fd6126533bb9c8a6092b88753bbf3edb4314633959a7f31d5f993ec91
- Size of remote file:
- 1.68 GB
- SHA256:
- c9da6bb7af2ee9504d6ec0d4357797f96b016ca0a79f83304d048949bdacb3a3
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