TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

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

Results

1 similar post found

Search: #xquest

当前筛选 #xquest清除筛选
Crypto News & Web3 Events | TON Ecosystem

@tonevents_en · Post #1290 · 02/27/2025, 10:44 AM

✉ xQuest — What's Next? 💬The Earn phase in xQuest Launch has officially ended. Over 125,000 users completed various quest tasks: from learning basic xRocket features to mastering trading and staking. This impressive result demonstrates high interest in the new platform. ⏺➕Now the Calculationphase is going, during which the campaign results will be summarize. 💰 After calculations, the Сlaim phase will begin – from March 3rd to March 10th, participants of the first xQuest campaign can claim their earned rewards and share the prize pool of 300,000 $XROCK (~$7750). Trade on xRocket exchange #xQuest#xRocket