Worked on enhancing large-model deployment capabilities in the binary-husky/trl repository by integrating VLLM and improving model transfer reliability. Developed a new transfer path supporting zero3+peft configurations, enabling seamless migration of very large models to VLLM while preventing GPU out-of-memory errors. Refactored the VLLMClient initialization and introduced a specialized adapter-merge method for DeepSpeed ZeRO Stage 3, addressing the complexities of distributed systems and model training at scale. Improved argument handling in the grpo_trainer workflow, eliminating runtime errors and increasing deployment stability. Utilized Python and deep learning frameworks to deliver maintainable, production-ready solutions for scalable model deployment.