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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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@amazingeo · Post #630 · 02/13/2026, 08:31 PM
🌍 Tokyo’s Shinjuku train station is the world’s busiest, with over 3.5 million passengers passing through daily. Its vast underground networks are so complex that some exits are kilometers apart. ✨ #urbanization⚡#infrastructure⚡#transit⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography 👉more Channels
@amazingeo · Post #87 · 08/21/2025, 03:12 AM
🌍 Tokyo’s rail system is so efficient that over 13 billion train trips are made each year within the city. This high-capacity network helps keep the world’s largest metropolitan area moving smoothly. ✨ #Tokyo⚡#transit⚡#urban⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography🌍
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