Developed and integrated an EAGLE3 compatibility layer for the Qwen2 model within the sgl-project/sglang repository, focusing on enhancing model interoperability and future extensibility. The work involved introducing a new flag to capture auxiliary hidden states and implementing a method for selective layer capture, modifying the model’s forward pass to support these features. Leveraging deep learning and machine learning expertise, the developer concentrated on Python-based model integration, ensuring the codebase is prepared for additional EAGLE3 features and broader compatibility. No major bugs were addressed during this period, as efforts centered on robust feature delivery and maintaining high code quality.