Worked on expanding model support within the linkedin/Liger-Kernel repository by integrating the Hugging Face Llava model with the existing Liger kernel. This involved implementing new Python components, patching the Llava forward pass, and aligning it with the kernel’s loss functions to maintain compatibility with current optimizations. The integration enabled seamless use of Llava within established workflows, preserving performance characteristics and ensuring smooth model deployment. Leveraged deep learning expertise, model integration techniques, and proficiency in Python to deliver this feature. The work focused on technical depth, addressing both architectural and compatibility challenges to support advanced large language model capabilities.