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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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⚪️ BHero Launchpad ⚪️ 🚀 Phase 2 🚀 After hints have been shared here and there with the community, we are officially announcing that the BHero Launchpad is entering Phase 2. Leveling up switches to BHAT-only mode. Learn more: https://blog.bhero.com/phase2/ 🕊 Twitter: Click Here 📘 Facebook: Click Here 💼 Linkedin: Click Here 🔼 Telegram Groups: EN / RO / FR 🎩Hats off! #launchpad#promotion#BHero