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<h3>Unified Multimodal Discrete Diffusion</h3>

[Alexander Swerdlow](https://aswerdlow.com/)<sup>1&#42;</sup>&nbsp;
[Mihir Prabhudesai](https://mihirp1998.github.io/)<sup>1&#42;</sup>&nbsp;
[Siddharth Gandhi](hhttps://www.ssgandhi.com/)<sup>1</sup>&nbsp;
[Deepak Pathak](https://www.cs.cmu.edu/~dpathak/)<sup>1</sup>&nbsp;
[Katerina Fragkiadaki](https://www.cs.cmu.edu/~katef/)<sup>1</sup>&nbsp;
<br>

<sup>1</sup> Carnegie Mellon University&nbsp;
 
[![ArXiv](https://img.shields.io/badge/ArXiv-<2503.20853>-<COLOR>.svg)](https://arxiv.org/abs/2503.20853) [![Webpage](https://img.shields.io/badge/Webpage-UniDisc-<COLOR>.svg)](https://unidisc.github.io/) 

<!-- [![Demo](https://img.shields.io/badge/Demo-Custom-<COLOR>.svg)](https://huggingface.co/spaces/todo) -->
  
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## Hugging Face models

The UniDisc checkpoints are available on Hugging Face:
* [Interleaved Image-Text](https://huggingface.co/aswerdlow/unidisc_interleaved)
* [Non-Interleaved (Static)](https://huggingface.co/aswerdlow/unidisc_non_interleaved)

## Getting Started

To install the dependencies, run:
```bash
git submodule update --init --recursive
uv sync --no-group dev
uv sync
```

For a more detailed installation guide, please refer to [INSTALL.md](docs/INSTALL.md).

## Data

See [DATA.md](docs/DATA.md) for details on how to download and preprocess the datasets. We provide processing scripts and instructions for all of the used datasets. Additionally, we release a synthetic dataset available [here](https://huggingface.co/datasets/aswerdlow/unidisc_hq) and the corresponding [generation scripts](unidisc/datasets/preprocessing/unidisc_dataset/README.md) as well as the raw data.

## Training

See [TRAIN.md](docs/TRAIN.md) for training commands.

## Inference

Interactive demo:
```bash
mkdir -p ./ckpts/unidisc_interleaved
huggingface-cli download aswerdlow/unidisc_interleaved --local-dir ./ckpts/unidisc_interleaved
uv run demo/server.py experiments='[large_scale_train,large_scale_train_high_res_interleaved,eval_unified,large_scale_high_res_interleaved_inference]' trainer.load_from_state_dict="./ckpts/unidisc_interleaved/unidisc_interleaved.pt"
uv run demo/client.py
```

## Training

See [TRAINING.md](docs/TRAINING.md) for details.

## Evaluation

See [EVAL.md](docs/EVAL.md) for details.


### Citation
To cite our work, please use the following:
```
@article{swerdlow2025unidisc,
  title = {Unified Multimodal Discrete Diffusion},
  author = {Swerdlow, Alexander and Prabhudesai, Mihir and Gandhi, Siddharth and Pathak, Deepak and Fragkiadaki, Katerina},
  journal = {arXiv preprint arXiv:2503.20853},
  year = {2025},
  doi = {10.48550/arXiv.2503.20853},
}
```

## Credits

This repository is built on top of the following repositories:

- [MDLM](https://github.com/kuleshov-group/mdlm)
- [Lumina-T2X](https://github.com/Alpha-VLLM/Lumina-T2X)