Add model card with metadata and links
#1
by
nielsr
HF Staff
- opened
README.md
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---
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pipeline_tag: image-text-to-text
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library_name: diffusers # This might need to be verified in the repo.
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license: mit # Placeholder - update if needed
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---
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<div align="center">
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<br>
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<img src="docs/images/banner.webp" width="1000">
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<h3>Unified Multimodal Discrete Diffusion</h3>
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[Alexander Swerdlow](https://aswerdlow.com/)<sup>1*</sup>
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[Mihir Prabhudesai](https://mihirp1998.github.io/)<sup>1*</sup>
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[Siddharth Gandhi](hhttps://www.ssgandhi.com/)<sup>1</sup>
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[Deepak Pathak](https://www.cs.cmu.edu/~dpathak/)<sup>1</sup>
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[Katerina Fragkiadaki](https://www.cs.cmu.edu/~katef/)<sup>1</sup>
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<br>
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<sup>1</sup> Carnegie Mellon University
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[](https://arxiv.org/abs/2503.20853) [](https://unidisc.github.io/)
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<!-- [](https://huggingface.co/spaces/todo) -->
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</div>
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## Hugging Face models
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The UniDisc checkpoints are available on Hugging Face:
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* [Interleaved Image-Text](https://huggingface.co/aswerdlow/unidisc_interleaved)
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* [Non-Interleaved (Static)](https://huggingface.co/aswerdlow/unidisc_non_interleaved)
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## Getting Started
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To install the dependencies, run:
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```bash
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git submodule update --init --recursive
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uv sync --no-group dev
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uv sync
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```
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For a more detailed installation guide, please refer to [INSTALL.md](docs/INSTALL.md).
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## Data
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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.
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## Training
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See [TRAIN.md](docs/TRAIN.md) for training commands.
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## Inference
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<!-- Inference demo for **TODO**.
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```
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TODO
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``` -->
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<!-- <img src="docs/todo.png" width="1000"> -->
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Interactive demo:
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```
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python demo/server.py
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python demo/client_simple_fasthtml.py
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```
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## Training
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See [TRAINING.md](docs/TRAINING.md) for details.
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## Evaluation
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See [EVAL.md](docs/EVAL.md) for details.
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### Citation
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To cite our work, please use the following:
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```
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@article{TODO,
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title={TODO},
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author={TODO},
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journal={arXiv preprint arXiv:TODO},
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year={TODO}
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}
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```
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## Credits
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This repository is built on top of the following repositories:
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- [MDLM](https://github.com/kuleshov-group/mdlm)
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- [Lumina-T2X](https://github.com/Alpha-VLLM/Lumina-T2X)
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