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Source channel @githubtrending · Post #15340 · Dec 17

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#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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@dianjingtiyuxieyi · Post #5657 · 09/06/2025, 02:23 PM

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刀塔-TI国际邀请赛 #BOOM 对战 Wildcard (BO3) 2025-09-06 19:00 第三局获胜： BOOM 第三局击杀让分：BOOM -11.5 第三局击杀大小： 小于42.5 （重心） 第三局时间大小： 小于39 第一滴血： BOOM

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@dianjingtiyuxieyi · Post #5655 · 09/06/2025, 12:46 PM

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刀塔-TI国际邀请赛 #BOOM 对战 Wildcard (BO3) 2025-09-06 19:00 第二局获胜： BOOM 第二局击杀让分：BOOM -11.5 （重心） 第二局击杀大小： 大于41.5 第二局时间大小： 小于38 第一滴血： BOOM

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@dianjingtiyuxieyi · Post #5647 · 09/06/2025, 11:15 AM

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刀塔-TI国际邀请赛 #BOOM 对战 Wildcard (BO3) 2025-09-06 19:00 第一局获胜： BOOM 第一局击杀让分：BOOM -9.5 第一局击杀大小： 小于44.5 （重心） 第一局时间大小： 小于39 第一滴血： BOOM

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@dianjingtiyuxieyi · Post #5627 · 09/05/2025, 05:35 PM

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刀塔-TI国际邀请赛 #BOOM 对战 Nemesis (BO3) 2025-09-05 22:00 第二局获胜：Nemesis 第二局击杀让分：Nemesis+6.5 第二局击杀大小：小于43.5 （重心） 第二局时间大小：小于40 第一滴血：BOOM

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@dianjingtiyuxieyi · Post #5617 · 09/05/2025, 04:39 PM

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刀塔-TI国际邀请赛 #BOOM 对战 Nemesis (BO3) 2025-09-05 22:00 第一局获胜：BOOM 第一局击杀让分：BOOM-3.5 第一局击杀大小：小于44.5 第一局时间大小：小于41 （重心） 第一滴血：BOOM

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@mountstorm · Post #238 · 06/15/2022, 08:23 AM

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#boom I guess, it is good for the first time) 😋 Next time I do my best to 7.0 + 💪 📅 12.06.2022 Mock exam - Band 6.5

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