Developed and integrated the Qwen2ForSequenceClassification model into the IBM/vllm repository, expanding its sequence classification capabilities. Focused on model development using Python and PyTorch, the work involved implementing new classification methods within the model and corresponding test files to ensure reliability and correctness. Documentation was updated to guide users on the inclusion and usage of the new model, supporting broader adoption and ease of integration. No critical bugs were addressed during this period, as the primary emphasis was on delivering a robust feature. The contribution demonstrates depth in deep learning and machine learning, with attention to maintainability and usability.