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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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Libreware

@libreware · Post #1561 · 02/27/2026, 10:14 PM

#Droidify#Fdroid client Added SHA256 for signature verification (Long press on Sync icon to refresh index) https://github.com/Droid-ify/client/releases Many more android app stores at https://t.me/Libreware/1132 and #apk@LibreWare Tell us your favorite or any missing ones

Libreware

@libreware · Post #997 · 10/27/2021, 12:22 AM

Droid-ify Unofficial F-Droid client with Material UI based on Foxy-Droid Features: Material F-Droid style No cards or inappropriate animations Fast repository syncing Standard Android components and minimal dependencies https://github.com/iamlooker/Droid-ify/ Download: https://github.com/Iamlooker/Droid-ify/releases https://f-droid.org/packages/com.looker.droidify https://android.izzysoft.de/repo/apk/com.looker.droidify 📡@NoGoolag📡@Libreware #droidify#apk#fdroid