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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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@TossLabChannel · Post #424 · 12/22/2024, 03:30 AM

#局域网唤醒#SvelteKit#Go#PocketBase 简单局域网唤醒 Web 应用程序 该应用程序利用 SvelteKit、Go 和 PocketBase 构建,适合家庭或企业环境中需要设备唤醒和管理的用户。 ✨ 特点 • 🚀 一键设备唤醒仪表板 • ⏰ 定时事件自动化(通过 Cron 设置) • 🔌 支持 Ping 任意端口 • 🔍 网络扫描发现设备(需要 nmap) • 👤 安全的用户管理 • 🌐 多语言支持(i18n) • 🎨 提供 29 种主题 • 🐳 支持多平台 Docker 镜像 • 🏠 完全自托管 📢 群聊: @TossLab 🎈 频道: @TossLabChannel ❤️不想错过精彩内容,请打开 #频道通知,你的 #阅读#点赞#转发 便是我发帖的最大动力!