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, follow the guides in this order:

  1. Why Use NeMo-Run? — Understand the benefits and philosophy.

  2. Quickstart — Get something running in 5 minutes.

  3. Configuration — Learn how to configure tasks and experiments.

  4. Execution — Understand executors, packagers, and launchers.

  5. Executors — Per-executor guides from local to cloud.

  6. Management — Track, inspect, and reproduce past experiments.

Advanced Topics#

  • CLI Reference — Automate experiment management from the command line.

  • Ray Integration — Distributed Ray workloads on Kubernetes, Slurm, and Lepton.

  • Architecture — Internals for contributors and power users.

Core Concepts#

NeMo-Run is built around three core responsibilities:

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

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

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