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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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Repositorio data science

@repo_science · Post #3567 · 09/06/2023, 07:13 PM

#python#dataEngineering 📃 Amazon Web Services in Action Description Master essential best practices for deploying and managing applications on Amazon Web Services. This revised bestseller is packed with techniques for building highly available and scalable architectures and automating deployment with Infrastructure as Code. ⚖️1.7 GB 🔗Enlace ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----

Repositorio data science

@repo_science · Post #3495 · 08/03/2023, 01:47 PM

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Repositorio data science

@repo_science · Post #3084 · 04/21/2023, 02:49 PM

#apacheSpark#ETL#dataEngineering#Python 🎚 Apache Spark 3 for Data Engineering and Analytics with Python [Video] 🗣David Mngadi 🌐 Inglés ⚖️2.1GB 🔗Link ----- Canal principal:@repo_science Cupones: @freecoupons_reposcience -----