Instructions to use Rostlab/prot_bert_bfd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rostlab/prot_bert_bfd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rostlab/prot_bert_bfd")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Rostlab/prot_bert_bfd", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Rostlab/prot_bert_bfd: direct link, hf CLI and curl.
- Browser
- Download file 1.68 GB
-
https://huggingface.co/Rostlab/prot_bert_bfd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Rostlab/prot_bert_bfd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Rostlab/prot_bert_bfd/resolve/main/pytorch_model.bin
1.68 GB
- Xet hash:
- 6ad486881890213c70fb7081dafb83432303136bdafd7acd255d24a7558816ae
- Size of remote file:
- 1.68 GB
- SHA256:
- 89a5b439bde4df5e6b09a7e568066a66eabacb69cbca6cbae59e98f9756db804
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