| license: mit | |
| tags: | |
| - diffusion | |
| - world-models | |
| - video-generation | |
| - carracing | |
| - reinforcement-learning | |
| - pytorch | |
| # Interactive Diffusion: A Playable World Model | |
| This repository hosts the trained model weights and sample data for the project [**Demystifying World Models: A Playable Diffusion Model**](https://github.com/nlml/interactive-diffusion). | |
| - **Blog Post**: [A Playable Diffusion Model](https://nlml.github.io/generative-models/interactive-diffusion-1/) | |
| - **GitHub Repository**: [nlml/interactive-diffusion](https://github.com/nlml/interactive-diffusion) | |
| ## Contents | |
| - `model.pt`: 145 MB checkpoint (optimizer stripped) of the `CausalSpatiotemporalDiT` trained with context noise augmentation (50,000 steps). | |
| - `sample_data/`: Sample shard 0 (`shard_00000_*`) containing gameplay frames, actions, and valid episode masks collected from `CarRacing-v3`. | |
| ## Quickstart | |
| Clone the GitHub repository and run the live driving server: | |
| ```bash | |
| git clone https://github.com/nlml/interactive-diffusion.git | |
| cd interactive-diffusion | |
| pip install -e . | |
| # Run the live interactive driving server: | |
| python webapp/server.py --checkpoint nlml/interactive-diffusion --data_dir ./carracing_data | |
| ``` | |