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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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@priborpedals · Post #560 · 10/29/2025, 08:12 AM

А вы знали, что Руководство по эксплуатации модуля Прибор Эксперимент представляет собой сувенирную коллекционную открытку? ️💌 #eurorack#vco#vcf @priborpedals

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@pptdaily · Post #5 · 01/18/2019, 08:56 AM

vcftools基于的是使用bgzip压缩过的vcf.gz文件,还需要用tabix进行index。将多个vcf样本进行merge使用vcf-merge命令,将同一样本的不同vcf整合使用vcf-concat #vcf#vcftools#snp