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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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Libreware

@libreware · Post #1185 · 09/26/2023, 11:04 PM

Meshenger is a P2P Android phone app that started out as a demo for community mesh networks. Meshenger started out as an idea to promote off the grid mesh networks and has now reached its initial goal. In this talk I will talk about the idea behind it, the story how it came to be and of course how it works. https://media.ccc.de/v/camp2023-57107-meshenger #P2P#Meshenger#Mesh#MeshNetwork#ChaosComputerClubBerlin #CCCde