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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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KYVE Announcements

@kyveannouncements · Post #322 · 06/20/2023, 04:04 PM

💫 With our first mainnet data pool now live, making CosmosHub chain data trustless for the #interchain ecosystem, what blockchain should we start archiving & validating next? 🤔 Tag them in the comments below! 💬👇 https://twitter.com/KYVENetwork/status/1671187001075277825

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KYVE Announcements

@kyveannouncements · Post #356 · 12/18/2023, 04:02 PM

KYVE is partnering with Syntropynet! Taking #interchain data to new bounds 💫 🤝 In the spirit of the #modular era, Syntropy & KYVE are each bringing forward their specialized data solutions to ensure a reliable, full-scope data experience from start to finish for both historical & real-time data streams. Learn more about this exciting partnership ⤵️ https://x.com/KYVENetwork/status/1736776359043539058?s=20