 FAT, Peptide Hypergraph Attention Network, is a deep learning framework designed to accurately predict peptide secondary structures. It combines residual level reasoning with structural semantic information from multiple sources to improve performance on short peptides. Additionally, it provides interpretability by highlighting the reasoning behind its predictions. This makes it suitable for use in drug discovery and other applications where accurate secondary structure prediction is important.