Feature Extraction
Transformers
Safetensors
protenrich
proteins
bioinformatics
drug-discovery
custom_code
Instructions to use SaeedLab/ProtEnrich-ESMC-600M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/ProtEnrich-ESMC-600M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/ProtEnrich-ESMC-600M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaeedLab/ProtEnrich-ESMC-600M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 3335a8a
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Browse files
README.md
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@@ -12,9 +12,6 @@ protenrich = AutoModel.from_pretrained("SaeedLab/ProtEnrich-ESMC-600M", trust_re
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seqs = "MKTFFVLLL"
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protein = ESMProtein(sequence=seqs)
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seqs = [" ".join(i) for i in seqs]
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inputs = tokenizer(seqs, return_tensors="pt", padding=True)
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with torch.no_grad():
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protein_tensor = client.encode(protein)
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outputs = client.logits(
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seqs = "MKTFFVLLL"
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protein = ESMProtein(sequence=seqs)
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with torch.no_grad():
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protein_tensor = client.encode(protein)
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outputs = client.logits(
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