Create README.md

README.md

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+---
+pipeline_tag: image-to-text
+license: apache-2.0
+tags:
+- Non-Autoregressive
+- Masked-Generative-Transformer
+- Discrete-Diffusion
+- Unified-Model
+language:
+- en
+---
+
+# Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model
+
+[Paper](https://arxiv.org/abs/2505.23606) | [Model](https://huggingface.co/MeissonFlow/Muddit) | [Code](https://github.com/M-E-AGI-Lab/Muddit) | [Demo](https://huggingface.co/spaces/MeissonFlow/muddit)
+
+
+![Tracing the Evolution of Unified Generation Foundation Models](./Evolution.png)
+
+
+## Introduction
+Welcome to the official repository of **Muddit** — a next-generation foundation model in the Meissonic family, built upon discrete diffusion for unified and efficient multimodal generation.
+
+Unlike traditional autoregressive methods, **Muddit** leverages discrete diffusion (a.k.a. MaskGIT-style masking) as its core mechanism — enabling fast, parallel decoding across modalities.
+
+While most unified models are still rooted in language priors, **Muddit** is developed from a visual-first perspective for scalable and flexible generation.
+
+Muddit (512) and Muddit Plus (1024) aim to handle diverse tasks across modalities -- such as text generation, image generation, and vision-language reasoning -- within a single architecture and decoding paradigm.
+
+## Usage
+
+Please refer to [github link](https://github.com/M-E-AGI-Lab/Muddit).
+
+## Citation
+If you find this work helpful, please consider citing:
+```bibtex
+@article{shi2025muddit,
+  title={Muddit: Liberating generation beyond text-to-image with a unified discrete diffusion model},
+  author={Shi, Qingyu and Bai, Jinbin and Zhao, Zhuoran and Chai, Wenhao and Yu, Kaidong and Wu, Jianzong and Song, Shuangyong and Tong, Yunhai and Li, Xiangtai and Li, Xuelong and others},
+  journal={arXiv preprint arXiv:2505.23606},
+  year={2025}
+}
+```