Worked on the rwth-i6/i6_models repository to improve the reliability and configuration correctness of the LSTM Block V1 component. Focused on debugging and maintaining code quality, the main contribution involved identifying and fixing a configuration access typo that affected the use of the enforce_sorted parameter. This targeted Python fix ensured that model training pipelines accessed configuration settings correctly, preventing misconfiguration and supporting stable model behavior. Leveraging skills in deep learning, machine learning, and model development, the work reinforced predictable operations across environments. The approach emphasized careful validation and low-risk changes, contributing to the robustness of the model development workflow.