Feature Extraction
Transformers
Safetensors
protenrich
proteins
bioinformatics
drug-discovery
custom_code
Instructions to use SaeedLab/ProtEnrich-ESM1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/ProtEnrich-ESM1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/ProtEnrich-ESM1b", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaeedLab/ProtEnrich-ESM1b", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 77ca842
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README.md
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tokenizer = AutoTokenizer.from_pretrained('facebook/esm1b_t33_650M_UR50S')
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encoder = AutoModel.from_pretrained("facebook/esm1b_t33_650M_UR50S")
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protenrich = AutoModel.from_pretrained("SaeedLab/ProtEnrich-
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seqs = ["MKTFFVLLL"]
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seqs = [" ".join(i) for i in seqs]
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tokenizer = AutoTokenizer.from_pretrained('facebook/esm1b_t33_650M_UR50S')
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encoder = AutoModel.from_pretrained("facebook/esm1b_t33_650M_UR50S")
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protenrich = AutoModel.from_pretrained("SaeedLab/ProtEnrich-ESM1b", trust_remote_code=True)
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seqs = ["MKTFFVLLL"]
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seqs = [" ".join(i) for i in seqs]
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