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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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Architectural Shovel / Любовь Дмитриева

@arch_shovel · Post #550 · 08/04/2022, 07:31 PM

P E A C E F U L / Grooming Retreat by Gartnerfuglen + Mariana de Delás The #minimalspace (3x3 meters footprint), functions as a #groomingretreat for one person. The structure, made by local #timberframes , elevates the cocoon to have exclusive views whilst giving a sense of translucent privacy to the user. . Layers of white netting frames are interlaced throughout the interior to grant different opacities for each specific use. The subtle introvertness of the structure encourages the user to take a break from the multitasking contemporary madness, and centre on individual mental and bodily hygiene. With importance on grooming’s #meditative (not cosmetic) qualities, the space inspires the user to devote time to the reconnection of the mind to the shell. #arch_shovel#architecture#archidaily