Hugging Face 发布智能体后训练五步课程
原标题：A curriculum for post-training agents
AI 摘要
Hugging Face 博客发布了一份面向智能体后训练（post-training agents）的课程指南，将后训练方法组织为五个步骤：SFT、蒸馏、强化学习、RL 环境和智能体运行框架（harness）与规模化。课程以训练编码智能体为贯穿示例，每一步都配有方法示意图、直播或幻灯片、博客文章和 TRL 文档，并对应 SFTTrainer、DistillationTrainer、GRPOTrainer、AsyncGRPOTrainer 等训练器。该课程强调智能体训练需要覆盖多轮工具调用与结果反馈的完整序列，而非单轮回答，为开发者提供了从模仿学习到在真实环境中强化学习的系统化路径。
正文节选
Post-training refers to the training stages that follow pretraining, such as supervised fine-tuning, distillation and reinforcement learning. These stages turn a pretrained model into one that follows instructions, uses tools or solves a specific task. When a model acts as an agent, it works over many turns. It calls tools, reads the results and decides what to do next. Agentic post-training applies these stages to agents, so training has to account for the whole sequence of turns instead of a s