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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 #14969 · 07/17/2025, 11:30 AM

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#cplusplus#artificial_intelligence#cloud#cloud_native#cncf#container#docker#edge_computing#ewasm#hacktoberfest#hacktoberfest2023#kubernetes#rust_lang#serverless#wasm#webassembly WasmEdge is a fast, lightweight, and secure WebAssembly runtime that lets you run programs safely on your devices, servers, or the cloud. It supports many programming languages like C++, Rust, and JavaScript, and can run AI models, microservices, and smart contracts efficiently. WasmEdge offers strong security by isolating programs, making it great for extending software safely. It works well on edge devices, smart devices, and cloud environments, and supports easy integration with tools like Kubernetes and Docker. Using WasmEdge helps you run powerful applications faster, safer, and more flexibly on various platforms[1][2][3][4][5]. https://github.com/WasmEdge/WasmEdge

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