Instructions to use AI4Protein/deep_bpe_1600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4Protein/deep_bpe_1600 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AI4Protein/deep_bpe_1600")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AI4Protein/deep_bpe_1600") model = AutoModelForMaskedLM.from_pretrained("AI4Protein/deep_bpe_1600", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#3)
Verified signature- Adding `safetensors` variant of this model (4985f2c0e083e6a6e24c9d65cd10be309eba34ad) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>14c0c8d
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Add model card for VenusFactory RoFormer model (#2)
Verified signature- Add model card for VenusFactory RoFormer model (9e6173d3f66e0ac8ce052e938d490be7d5d559fa) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>b4956f0
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initial commit
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