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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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@githubtrending · Post #15431 · 01/23/2026, 01:30 PM

#cplusplus#3d_engine#arm64#cmake#cplusplus#cpp17#d3d11#directx#directx11#engine#game#game_engine#gamedev#mod#opengl#opensource#sdl#sdl2#stalker#x64#xray_engine OpenXRay is a free, improved version of the X-Ray Engine for S.T.A.L.K.E.R. games like Call of Pripyat and Clear Sky. It adds 64-bit support, higher FPS, bug fixes, modding tools, and runs on Linux, macOS, and more. This benefits you with smoother, more stable gameplay, better performance on modern or non-Windows PCs, and easy access to new mods without changing the classic feel. https://github.com/OpenXRay/xray-16