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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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djangoproject

@djangoproject · Post #520 · 12/11/2017, 11:35 AM

https://goo.gl/CMGAqy If you know the #ropes, good news! Firefox now has support for #headless mode, making it easier to use as a backend to #automated tools. You can jump ahead to learn how to use it. Browser #automation is not a new idea, but is an increasingly important part of how modern websites are built, #tested, and #deployed. #Automation setups range from scripts run on local machines to vast deployments of specialized servers running in the cloud. To this end, browsers have long supported some level of automated control, usually via third-party driver software.