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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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EKOLOG.UZ| ENG

@ekologuzenglish · Post #10556 · 11/29/2025, 08:02 AM

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Fergana Region, Fergana District, Mindonobod Neighborhood: We can’t breathe, please help! Our homes are located near an asphalt plant, and due to its operations, dust and emissions enter our homes every day. If you step outside around 5–6 a.m., you can see the air is covered in haze. This situation seriously affects the health of our children: allergies and respiratory problems are increasing. We have repeatedly submitted complaints through the clinic, neighbors, and other organizations, and sent letters to higher authorities, but no measures have been taken. The environmental agency has also failed to address the problem. In addition, next to the asphalt plant, there are Megamix and Alibaster production facilities, whose emissions further worsen the air quality. We are calling on the public and responsible authorities: please pay attention to this air pollution and the threat it poses to our children’s health, and take the necessary measures! #Fergana#Mindonobod#Environment#AirPollution#ChildHealth#AsphaltPlant ☘️ Follow the latest environmental news on @ekologuz. Send your suggestions and feedback via @eklguz_bot.

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