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Cosmos Cookbook

Documentation Contributing

A comprehensive guide for working with the NVIDIA Cosmos ecosystemβ€”a suite of World Foundation Models (WFMs) for real-world, domain-specific applications across robotics, simulation, autonomous systems, and physical scene understanding.

πŸ“š View the Full Documentation β†’ β€” Step-by-step workflows, case studies, and technical recipes

carousel.mp4

Latest Updates

Recipe Model Description
Sports Video Generation Cosmos Predict 2.5 LoRA post-training for sports video generation with improved player dynamics and rule coherence
Distilling Cosmos Predict 2.5 Cosmos Predict 2.5 Model distillation using DMD2 to create a 4-step student model
Smart City SDG Pipeline Cosmos Transfer 2.5 + Reason 1 End-to-end synthetic data generation for traffic scenarios with CARLA
Temporal Localization for MimicGen Cosmos Reason 1 Automated timestamp annotation for robot learning data generation
BioTrove Moths Augmentation Cosmos Transfer 2.5 Domain transfer pipeline for scarce biological datasets using FiftyOne

Prerequisites

Use Case Linux (Ubuntu) macOS Windows
Running cookbook recipes (GPU workflows) βœ… Supported ❌ ❌
Local documentation & contribution βœ… Supported βœ… Supported ⚠️ WSL recommended

For Documentation & Contribution (All Platforms)

  • Git with Git LFS
  • Python: Version 3.10+
  • Internet access for cloning and dependencies

For Running Cookbook Recipes (Ubuntu Only)

Full GPU workflows require an Ubuntu Linux environment with NVIDIA GPUs.

β†’ See Getting Started for complete hardware and software requirements.

Quick Start

1. Install Git LFS (Required)

⚠️ Important: This repository contains many media files (videos, images, demonstrations). Git LFS is required to clone and work with this repository properly.

# Ubuntu/Debian (recommended)
sudo apt update && sudo apt install git-lfs

# Enable Git LFS globally
git lfs install

For other platforms (macOS, Windows, Fedora), see the official installation guide at git-lfs.com.

If you've already cloned without LFS, fetch the media files with:

git lfs pull

2. Install System Dependencies

# Install uv (fast Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh
source $HOME/.local/bin/env

# Install just (command runner)
uv tool install -U rust-just

For other platforms, see astral.sh/uv for installation instructions.

3. Clone and Setup Repository

# Clone the repository
git clone https://github.com/nvidia-cosmos/cosmos-cookbook.git
cd cosmos-cookbook

# Install dependencies and setup
just install

4. Explore the Documentation

# Serve documentation locally
just serve-external  # For public documentation
# or
just serve-internal   # For internal documentation (if applicable)

Then open http://localhost:8000 in your browser.

Repository Structure

The Cosmos Cookbook is organized into two main directories:

docs/

Contains the source documentation in markdown files:

  • Technical guides and workflows
  • End-to-end examples and case studies
  • Step-by-step recipes and tutorials
  • Getting started guides

scripts/

Contains executable scripts referenced throughout the cookbook:

  • Data processing and curation pipelines
  • Model evaluation and quality control scripts
  • Configuration files for post-training tasks
  • Automation tools and utilities

This structure separates documentation from implementation, making it easy to navigate between reading about workflows and executing the corresponding scripts.

Media File Guidelines

When contributing media files, prefer .mp4 over .gif:

  • Better quality β€” MP4 supports full color depth vs GIF's 256-color limit
  • Smaller file size β€” Modern video codecs compress far more efficiently
  • Audio support β€” MP4 can include narration when needed

Use H.264 encoding for universal browser compatibility.

Available Commands

# Development
just install          # Install dependencies and setup
just setup            # Setup pre-commit hooks
just serve-external   # Serve public documentation locally
just serve-internal   # Serve internal documentation locally

# Quality Control
just lint            # Run linting and formatting
just test            # Run all tests and validation

# Continuous Integration
just ci-lint         # Run CI linting checks
just ci-deploy-internal         # Deploy internal documentation
just ci-deploy-external         # Deploy external documentation

Contributing & Support

  • Contributing Guide - How to contribute to the cookbook
  • Report Issues: Use GitHub Issues for bugs and feature requests
  • Share Success Stories: We love hearing how you use Cosmos models creatively

License and Contact

This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.

NVIDIA Cosmos source code is released under the Apache 2 License.

NVIDIA Cosmos models are released under the NVIDIA Open Model License. For a custom license, please contact cosmos-license@nvidia.com.