In March 2025, JP42 Maru expanded model support in the linkedin/Liger-Kernel repository by integrating the Hugging Face Llava model. This work involved developing new Python components, patching the Llava forward pass, and aligning it with the Liger kernel’s loss functions to maintain compatibility with existing optimizations. Leveraging expertise in deep learning, large language models, and model integration, JP42 Maru ensured that the new model could be used seamlessly within established workflows. The integration preserved performance characteristics and required a deep understanding of both Hugging Face Transformers and the Liger kernel’s architecture, reflecting a focused and technically thorough engineering effort.