@moeshiro · Post #174 · 10/30/2025, 04:30 PM
试着接收了这次《三体》联动哈工大从阿斯图一号卫星上发送的 SSDV信号,只能说发送的图片真的好难看(),不过搭建解码环境的过程还是比较有趣的,也学会了 sdr 精准跟随卫星频率的操作。 #业余无线电#HAM#卫星#SSDV#ASRTU-1
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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