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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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Host Testing and evaluation

@HostEvaluate · Post #853 · 01/18/2023, 12:02 PM

#misaka#DE#BER Host Provider: Misaka Network Location: Berlin, Germany Specification: 1vCore(Xeon Skylake) | 512MB RAM | 10GB NVMe | 512GB Traffic | $10.5 / Mo Test IP: 45.131.71.128 MTR: https://ping.sx/mtr?p=misaka-ber02-s2c 感谢商家提供的测试机。这款是 Misaka 新上的柏林机器,带 CN2 优化。应该会有活动的。这个 CN2 是从他们俄罗斯牵过去的,延迟比咸鱼云的法兰克福要低些。国际目前只有 retn, 后面会加 lumen, 具体啥时候加上就不得而知了。去往西欧延迟更低的一个选择。机器性能可以,本地带宽应该是 10Gbps? BerlinCN2Launch 年付 30off, 限 CN2 产品 https://paste.red/p/c20e1103c9f5