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:
- fbf3151c747664ba053d25b5318b9b4ed19cfdbfab7e2121b5b5246bcc7fdf13
- Size of remote file:
- 1.68 GB
- SHA256:
- 89a5b439bde4df5e6b09a7e568066a66eabacb69cbca6cbae59e98f9756db804
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