NVIDIA/DreamDojo

Health v2 · maintenance only

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1059 stars · 75 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

NVIDIA's official PyTorch codebase for DreamDojo, a generalist robot world model pretrained on 44k hours of human egocentric video and post-trained on robot embodiments for action-conditioned video generation. It includes training, post-training, distillation, and evaluation pipelines plus pretrained 2B/14B checkpoints.

Use cases

• train a robot world model from human videos
• generate action-conditioned video rollouts for robot policies
• post-train a world model on a new robot embodiment
• distill a video world model for real-time interactive generation
• pretrain on large-scale egocentric video datasets
• evaluate world model generalization across robots and environments

When to choose

• you need a generalist robot world model with pretrained checkpoints
• you want to post-train a video world model on your own robot data
• you need real-time interactive world model rollouts via distillation
• you are doing research on video-based robot learning

When to avoid

• you need a lightweight CPU-only tool
• you want a production robot control stack rather than research code
• you lack multi-GPU resources for training or inference
• you need a non-research-licensed or turnkey commercial product

Facets

library · maturity active

machine-learning deep-learning video-processing simulation robotics llm-training data-science robotics machine-learning deep-learning artificial-intelligence simulation computer-vision python world-model robot-learning video-generation latent-action-model model-distillation egocentric-video research-code nvidia icml-2026 foundation-model linux gpu docker

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