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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 #14774 · 06/01/2025, 12:00 PM

#cplusplus#3mf#android#asset_pipeline#assets#assimp#c_plus_plus#collada#dae#fbx#fbx_exporter#game_development#gamedev_tool#gamedevelopment#gltf#gltf2#ifc#patreon#python#stl The Open Asset Import Library (Assimp) is a tool that helps load many different 3D file formats into a common format. It supports over 40 formats for importing and several for exporting. Assimp works on various platforms like Windows, macOS, Linux, Android, and iOS. It also provides tools to improve the 3D models, such as fixing errors and making them look better. This library is useful for developers because it simplifies working with different 3D file types, making it easier to create and manage 3D content across different systems. https://github.com/assimp/assimp