Key features delivered: - Gemma4ForCausalLM LoRA adapter loading and weight mapping implemented in red-hat-data-services/vllm-cpu. This enables loading of LoRA adapters, adds a mapping for LoRA weights, and ensures compatibility with the model architecture, improving fine-tuning usability and performance (commit 0ab0f70a91a6a0000a1b5af78cdf1e8e68266fc). - LoRA adapter loading support with weight mapping and tests added for Gemma4ForCausalLM in jeejeelee/vllm, including layer mappings for standard and mixture-of-experts configurations, enhancing adaptability and performance (commit 92feb9991d153bb36f2be802cc7eaac33f8f4695). Major bugs fixed: - Fixed loading of LoRA adapters for Gemma4ForCasualLM across the affected repositories, addressing the bugfix entry (#38844) and ensuring correct adapter loading (commits 0ab0f70a... and 92feb9991d...). Overall impact and accomplishments: - Achieved cross-repo enablement of LoRA-based fine-tuning for Gemma4ForCausalLM, improving usability, deployment flexibility, and model adaptability, while reducing integration friction in production pipelines. Technologies/skills demonstrated: - LoRA adapters, weight mapping, standard and MoE layer mappings, test-driven development, cross-repo collaboration, and version-controlled fine-tuning enhancements.