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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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@dopingram · Post #3150 · 07/24/2024, 08:38 AM

Робот-МАГ, digital art, Doping Pong, 2009 Персонаж, придуманный арт-группой Doping Pong для фирменного стиля Международного мультимедиа фестиваля MIGZ. Россия, Москва, кинотеатр 35MM, июнь 2009 года. Первые карандашные эскизы этого персонажа появились в 2001 году и ждали своего часа. #dopingpong#robot#mag#migz#multimedia