Developed a configurable enhancement for the fla-org/flash-linear-attention repository, introducing an option in the DeltaNet model to allow negative eigenvalues. This feature, implemented in Python and leveraging deep learning and machine learning expertise, expands the model’s flexibility for advanced experimentation without impacting existing deployments. The approach focused on backward compatibility by making the new behavior opt-in, ensuring current users experience no disruption. Delivered as a single, well-documented commit, the work demonstrates clear traceability and maintainability. This addition enables researchers and practitioners to explore edge-case scenarios and potentially realize performance improvements in specialized workloads through targeted model configuration.