multi-harness-rl
multi-harness-rl is Train open models with RL inside real agent harnesses. It is ranked #6730 on the AI Radar, in AI agents, first seen 35 days ago and shared in 22 posts (302.7k views).
What people said about multi-harness-rl on X
同一个 AI 模型，换个工具就犯傻？问题未必出在模型，可能出在 Harness 上！ Hugging Face 最近分享了个新思路：Multi-Harness RL（多环境强化学习）。 简单说，模型要是只在一套 Agent 工具里训练，很容易把特定的工具名、提示词和执行流程背下来。换到 Codex、OpenCode 这些环境，表现就可能打折扣。 研究团队把 OpenEnv、Harbor、TRL 串起来，让模型在多种真实 Harness 里训练。 实验里，LFM2.5-2.6B 的任务首轮解决率从 42.2% 提到 54.2%，工具调用次数还降了。 这说明关键一点：模型能力不只看参数，还看它在哪种环境里练出来的。 🔗…
— @Huahuazo, 11 days ago · 0 likes · see the post
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multi-harness-rl in numbers
- Rank on the AI Radar: #6730 of 10402
- Shared in 22 posts by 22 accounts: @Huahuazo
- 302.7k views on those posts
- First seen 35 days ago, last shared 11 days ago
- Pricing seen by AGK Intelligence: free
- Market: AI agents
FAQ
What is multi-harness-rl?
Train open models with RL inside real agent harnesses It was first shared on X 35 days ago and is ranked #6730 on the AI Radar.
Is multi-harness-rl free?
Yes, it is free to use.
Who shared multi-harness-rl?
22 accounts on X, including @Huahuazo, in 22 posts totalling 302.7k views.
Every post is read and classified by AGK Intelligence: what it is, which market it belongs to, and whether the link is a real tool. 65.6k posts from 5k X accounts over the last 14 days, 10.4k tools, 19 markets. New posts are collected several times an hour and the full ranking is recomputed every hour — last update 2026-11-06 15:10 UTC. Full method.