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Source channel @githubtrending · Post #15340 · Dec 17

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#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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@githubtrending · Post #15282 · 11/09/2025, 02:00 PM

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#shell#aesthetic#dark_mode#dynamic#hyde#hyprdots#light_mode#themes#unix_porn#wallpapers HyDE is a clean, modular, and visually appealing development environment designed for Hyprland on Arch Linux and some Arch-based distros. It offers easy installation via a script that auto-detects NVIDIA cards and configures necessary drivers, but it may conflict with existing desktop environments or theming. You can customize it with many official and community themes using a tool called themepatcher. HyDE keeps your configuration organized and separate from core scripts, making updates safer and simpler. It also supports running in a virtual machine for testing. Joining the HyDE Discord community helps you get support and share ideas. This setup benefits you by providing a stylish, maintainable, and customizable desktop environment with a smooth update process and community support. https://github.com/HyDE-Project/HyDE

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#shell#aesthetic#dark_mode#dynamic#hyde#hyprdots#light_mode#themes#unix_porn#wallpapers