Feature Extraction
Transformers
Safetensors
seqscreen
proteins
molecules
bioinformatics
drug-discovery
custom_code
Instructions to use SaeedLab/SeqScreen-Frozen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/SeqScreen-Frozen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/SeqScreen-Frozen", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaeedLab/SeqScreen-Frozen", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31bcd49baada3f14c2ff2735a7eaa27d487bf659de4e55ddb7681e8fd9d83afd
- Size of remote file:
- 8.93 MB
- SHA256:
- c1c541db2f8ae2d5e06ed1ab8d032278d818a8f4800880c482bc8b76600494a1
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