Worked on enhancing the Megatron-LM codebase, focusing on usability, reliability, and maintainability for both the ROCm and swiss-ai repositories. Delivered improved user guidance for the --hybrid-override-pattern option and expanded unit test coverage for Mamba hybrid model components, clarifying valid inputs and strengthening correctness for future development. Developed comprehensive unit tests for the mamba-hybrid-layer-allocation module, validating diverse scenarios and error handling to reduce regression risk. Employed Python, PyTorch, and CUDA, applying test-driven development and deep learning expertise to ensure robust model behavior and facilitate safe refactoring, with all work centered on feature development and documentation improvements.