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README.md

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-<div align="center">
-<br>
-<img src="docs/images/banner.webp" width="1000">
-<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) -->
-  
-</div>
-
-## 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)
+title: UniDisc Demo
+emoji: 🐢
+colorFrom: purple
+colorTo: blue
+sdk: docker
+pinned: false

demo/README.md

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-title: UniDisc Demo
-emoji: 🐢
-colorFrom: purple
-colorTo: blue
-sdk: docker
-pinned: false