精选理由
这篇分析硬核拆解RL训练效率瓶颈，vLLM+verl的沙箱实验值得一看。
SemiAnalysis对强化学习训练系统进行深度分析，指出效率关键在于匹配训练器与生成器的吞吐量。研究基于vLLM+verl框架，@KaichaoYou和Ao Shen进行了沙箱扩展实验。该工作建立在@KaichaoYou早期在OpenRLHF、verl、slime等框架的RL集成工作之上。
原文 · vLLM
A great deep dive from @SemiAnalysis_ on RL traini…
A great deep dive from @SemiAnalysis_ on RL training systems and how much RL efficiency comes down to matching trainer and generator throughput!
Shoutout to @KaichaoYou and Ao Shen from @inferact for the sandbox scaling experiments with vLLM + verl, building on @KaichaoYou's early RL integration work across OpenRLHF, verl, and slime🫡