2026年前沿模型如何基于结果进行训练

AI 摘要

本文是Hugging Face博客关于2026年前沿模型训练方式的补充材料，梳理了OpenAI、DeepSeek、Meta等实验室在强化学习（RL）后训练中的公开做法。文章指出，可验证奖励（RLVR）已成为主流，GRPO算法被广泛采用但多有修改，且RL正从单答案转向环境交互。作者通过引用各实验室报告，展示了这些模式如何贯穿从7B模型到前沿系统的训练流程。

正文节选

This article is complementary material for Class 3: Reinforcement Learning of the Training an Agent series Ben and I are doing, where we train a coding agent step by step. This article does not explain how GRPO works. The class does that, with the three experiments. Here we show where the same ideas appear in the reports of frontier labs. Previous classes: SFT on traces and distillation. It also pairs with Distillation in 2026 (so far), where we did the same exercise for distillation. Something

发布时间：—

抓取时间：2026-08-12 16:40

来源机构：Hugging Face