StackLLaMA：使用 RLHF 微調 LLaMA 模型的實戰指南
Original: StackLLaMA: A hands-on guide to train LLaMA with RLHF
This classic blog post from Hugging Face provides an extremely valuable hands-on guide for the open-source community, detailing how to…
本指南是 Hugging Face 介紹如何使用 TRL（Transformer Reinforcement Learning）與 PEFT（LoRA）技術，對 LLaMA 模型進行人類回饋強化學習（RLHF）的經典實戰教學。文章以 Stack Exchange 數據集為例，詳細拆解了監督式微調（SFT）、獎勵模型（RM）訓練，以及近端策略最佳化（PPO）三大核心步驟，展示了如何在有限的硬體資源下完成大語言模型的對齊（Alignment）訓練。
This classic blog post from Hugging Face provides an extremely valuable hands-on guide for the open-source community, detailing how to fine-tune the LLaMA model using Reinforcement Learning from Human Feedback (RLHF) to produce a model called StackLLaMA.
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