In April 2025, Jay Thakur developed support for the trim_logits parameter in the DeepseekV3 model within the HabanaAI/optimum-habana-fork repository. This feature enables selective processing of logits during inference, addressing performance and memory efficiency challenges in deep learning workflows. Jay implemented the solution using Python, leveraging expertise in model optimization and transformer models to ensure seamless integration with the existing codebase. The work focused on enhancing inference by reducing unnecessary memory usage, reflecting a targeted and technically sound approach. Although the contribution was limited to a single feature, it demonstrated depth in both deep learning and optimization techniques.