PypCoder/SERAPH
https://huggingface.co/PypCoder/SERAPHSERAPH is a deep learning model designed for 3-state (Q3) protein secondary structure prediction. It processes raw single amino acid sequences and predicts residue-level secondary structure states: Alpha Helix (H), Beta Sheet (E), or Coil/Loop (C).
Sourced from
- HuggingFace — PypCoder/SERAPH
Related resources
This model may be overfit to some extent (see below). Try running this notebook on the datasets linked to in the notebook. See if you can figure out why the metrics differ so much on the datasets. Is it due to something like sequence similarity in the train/test split?
Fine-tuned ESM-2 650M with LoRA for predicting protein subcellular localization (10 classes).
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