Instructions to use virtual-human-chc/prot_bert_bfd 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 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="virtual-human-chc/prot_bert_bfd")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("virtual-human-chc/prot_bert_bfd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cab48e63e89cacc7e8b129a8a7d44c8ddaa1d7c96e116333507279ef4a0ec29c
- Size of remote file:
- 1.85 GB
- SHA256:
- 85fd0091dec8e3fb7004920efcfb1de00365a9a038866f5d8bf756c2e0e86b40
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