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Thomas Wolf更新于 10月21日 22:46

Thomas Wolf 称赞 MiMo-V2.6 RL 训练开放度

Impressive level of openness on such a large run

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如此大规模训练能有这种开放程度,令人印象深刻。

引用

Fuli Luo

@_LuoFuli

Nearly half a year of silence. We spent it studying one problem: how far RL can scale. MiMo-V2.6 is in the middle of its RL run right now. Three things we scaled: compute (~2B tokens per step, 1568 prompts × 16 rollouts, fully async), environments and harnesses (multi-task agentic RL, mixed across multiple harnesses in one run), and grader compute (agentic…

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Nearly half a year of silence. We spent it studying one problem: how far RL can scale. MiMo-V2.6 is in the middle of its RL run right now. Three things we scaled: compute (~2B tokens per step, 1568 prompts × 16 rollouts, fully async), environments and harnesses (multi-task agentic RL, mixed across multiple harnesses in one run), and grader compute (agentic in-group credit assignment, with test-case and rubric-based rewards). We'll open-source the details piece by piece over the coming weeks. Streaming the run: https://t.co/ZSxahzJRju

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Impressive level of openness on such a large run

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Thomas Wolf