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Source channel @githubtrending · Post #15340 · Dec 17

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#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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📰 Info_Dota2

@Info_Dota2 · Post #36386 · 01/28/2025, 12:00 AM

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Yuma “Yuma” Langlet, hard carry de HEROIC, habló sobre el desempeño de su equipo tras avanzar a los playoffs del campeonato FISSURE PLAYGROUND #1. ¿Esperabas este resultado? “La verdad, no. No deberíamos haber jugado este torneo en primer lugar, ya que ni siquiera participamos en las clasificatorias. Tampoco nos preparamos específicamente, así que llegamos sin muchas expectativas. Solo estamos tratando de mostrar nuestro mejor nivel de juego y ver qué podemos lograr con eso.” Si así lo lograron sin preparación, ¿qué hubiera sido con entrenamiento previo? 🔥 #ESB#Esports#Dota2#Heroic#Yuma @Info_Dota2

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