Instructions to use Rostlab/prot_electra_generator_bfd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rostlab/prot_electra_generator_bfd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rostlab/prot_electra_generator_bfd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rostlab/prot_electra_generator_bfd") model = AutoModelForMaskedLM.from_pretrained("Rostlab/prot_electra_generator_bfd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Rostlab/prot_electra_generator_bfd: direct link, hf CLI and curl.
- Browser
- Download file 2.73 GB
-
https://huggingface.co/Rostlab/prot_electra_generator_bfd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Rostlab/prot_electra_generator_bfd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Rostlab/prot_electra_generator_bfd/resolve/main/pytorch_model.bin
2.73 GB
- Xet hash:
- 14c59ac0705542c6014c2a597e801a785cb6d76073c36a29a1ec951fa7e2e5f9
- Size of remote file:
- 2.73 GB
- SHA256:
- 5996013ba058f881374b84a49391c01f1b05999dbd20908ef60adbf86ad35140
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