BERT-HemoPep60 is a deep learning method based on transformer architecture and Domain Adaptive Pre-Training (DAPT) for quantitative prediction of peptide hemolytic activity against human red blood cells. The model employs an innovative prefix prompting approach that integrates experimental hemolysis data from multiple mammalian species and hemolysis indicators for peptide toxicity prediction.