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A new resource empowers users to fine-tune large language models (LLMs) locally on Windows using Group-Relative Policy Optimization (GRPO) and Hugging Face’s TRL library. This practical guide offers a complete workflow, including a ready-to-use script, optimized for consumer-grade GPUs. Key features include Low-Rank Adaptation (LoRA) and optional 4-bit quantization for efficient resource utilization, a robust reward system incorporating numeric, format, and boilerplate checks, automated data mapping compatibility with most Hugging Face datasets, and comprehensive troubleshooting tips tailored for local configurations. This initiative simplifies reinforcement learning experiments for AI enthusiasts and developers working on their own machines. The original discussion is available on Reddit: https://old.reddit.com/r/artificial/comments/1ms5mlw/a_guide_to_grpo_finetuning_on_windows_using_the/