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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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@storage_qi · Post #764 · 02/07/2024, 05:45 PM

#Clash#ClashMeta#WebUI#metacubexd#Yacd GH 页面自定义域:http://d.metacubex.one GH 页面:https://metacubex.github.io/metacubexd Cloudflare 页面:https://metacubexd.pages.dev 省流(个人认为体验优于Yacd): - 在Connections的功能相当丰富,功能体验最优(无法全部显示时,Shift+滚轮 可以横向滚动) - Proxies界面节点延迟可视化显示 - 还有一些其他Web UI所没有的功能 来源(ClashMeta官方支持)