Rohan Deshmukh contributed to the NVIDIA-NeMo/Automodel repository by developing a configurable hidden-states output feature for the NemotronHForCausalLM model. He implemented a parameterized approach in Python and PyTorch, allowing users to control whether hidden states are returned during model inference. To ensure reliability, he wrote comprehensive unit tests that validated the new output_hidden_states behavior and aligned these tests with existing CI and review standards. Rohan also addressed code quality by resolving ruff linting and formatting issues, cleaning up imports, and maintaining CI stability. His work demonstrated depth in deep learning model customization and robust testing practices within the codebase.