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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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#miaospeed#dev版 #4.3.2 ✅同步Miaospeed 4.3.1 ✅更新Clash内核 Clash v1.13.0 ✅修复STUN无法传参问题 ✅ipv6 stack 读取问题 ✅默认 ipv6 检测脚本换为更激进的[2606:4700:4700:.1111] ✅增加一个新的动态测速文件方式, DYNAMIC:ALL (欢迎提交测速文件地址) ❌尝试更新Clash.META内核失败,保留原本的版本

#miaospeed#release#v4.3.3 ✅同步Miaospeed 4.3.1 ✅更新Clash内核 Clash v1.13.0 ✅修复STUN无法传参问题 ✅PING和UDP的DNS预解析 ✅ipv6 stack 读取问题 ✅默认 ipv6 检测脚本换为更激进的[2606:4700:4700:.1111] ✅增加一个新的动态测速文件方式, DYNAMIC:ALL (欢迎提交测速文件地址) ✅Miaoko传入STUN或pingAddress无法解析自动切换Miaospeed内置地址 地址:https://github.com/moshaoli688/miaospeed/releases/tag/v4.3.3