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Source channel @githubtrending · Post #15340 · Dec 17

#python#gym#gym_environment#reinforcement_learning#reinforcement_learning_agent#reinforcement_learning_environments#rl_environment#rl_training NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior. https://github.com/NVIDIA-NeMo/Gym

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@tribebrook · Post #469 · 10/04/2025, 03:47 PM

#Mac#清理#GitHub#CleanMyMac#Lemon 🦡 像鼹鼠一样深入挖掘来清理您的 Mac 一;亮点 🐦深度系统清理- 一次性删除隐藏的缓存、日志和临时文件 📦彻底卸载- 清理了 22 个以上位置,而标准卸载只有 1 个,优于 CleanMyMac/Lemon ⚡️快速且轻量- 基于终端,零膨胀,带分页的箭头键导航 🧹海量空间恢复- 回收 100GB 以上的浪费磁盘空间 二;安装 curl -fsSL curl -fsSL https://raw.githubusercontent.com/tw93/mole/main/install.sh | bash 或者通过 Homebrew: brew install tw93/tap/mole GitHub地址:官方 🔔提示:限免,兑换码具有时效性,打开本频道通知,第一时间获取全网资讯!!! 🏠本消息Via:小小溪 📰群组:homeBrook 📢频道:Home_brook 🤖其他问题(投稿)请Bot:@xia0_bot