Guides#

Welcome to the NeMo-Run guides! This section provides comprehensive documentation on how to use NeMo-Run effectively for your machine learning experiments.

Get Started#

If you’re new to NeMo-Run, we recommend starting with:

  • Why Use NeMo-Run? - Understand the benefits and philosophy behind NeMo-Run.

  • Configuration - Learn how to configure your ML tasks and experiments.

  • Execution - Discover how to run your experiments across different computing environments.

  • Management - Master experiment tracking, reproducibility, and organization.

Advanced Topics#

For more advanced usage:

  • Ray Integration - Learn how to use NeMo-Run with Ray for distributed computing.

  • CLI Reference - Explore the command-line interface for NeMo-Run.

Core Concepts#

NeMo-Run is built around three core responsibilities:

  1. Configuration - Define your ML experiments using a flexible, Pythonic configuration system.

  2. Execution - Run your experiments seamlessly across local machines, Slurm clusters, cloud providers, and more.

  3. Management - Track, reproduce, and organize your experiments with built-in experiment management.

Each guide dives deep into these concepts with practical examples and best practices. Choose a guide above to get started!

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