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</p> </p>
<p align="center"> <p align="center">
<a href="https://github.com/VectorSpaceLab/OmniGen2"><img src="https://img.shields.io/badge/Project%20Page-OmniGen2-yellow" alt="project page"></a> <a href="https://vectorspacelab.github.io/OmniGen2"><img src="https://img.shields.io/badge/Project%20Page-OmniGen2-yellow" alt="project page"></a>
<a href=""><img src="https://img.shields.io/badge/arXiv%20paper-2409.11340-b31b1b.svg" alt="arxiv"></a> <a href="https://arxiv.org/abs/2506.18871"><img src="https://img.shields.io/badge/arXiv%20paper-2506.18871-b31b1b.svg" alt="arxiv"></a>
<a href=""><img src="https://img.shields.io/badge/HF%20Demo-🤗-lightblue" alt="demo"></a> <a href="https://github.com/VectorSpaceLab/OmniGen2?tab=readme-ov-file#-gradio-demo"><img src="https://img.shields.io/badge/Online%20Demo-🤗-blue" alt="demo"></a>
<a href="https://huggingface.co/spaces/OmniGen2/OmniGen2"><img src="https://img.shields.io/badge/HF%20Spaces-🤗-lightblue" alt="demo"></a>
<a href="https://huggingface.co/OmniGen2/OmniGen2"><img src="https://img.shields.io/badge/Model-🤗-yellow" alt="model"></a> <a href="https://huggingface.co/OmniGen2/OmniGen2"><img src="https://img.shields.io/badge/Model-🤗-yellow" alt="model"></a>
<a href=""><img src="https://img.shields.io/badge/Benchmark-🤗-yellow" alt="model"></a> <a href="https://huggingface.co/datasets/OmniGen2/OmniContext"><img src="https://img.shields.io/badge/Benchmark-🤗-yellow" alt="model"></a>
<a href=""><img src="https://img.shields.io/badge/Dataset-🤗-yellow" alt="model"></a> <a href="https://huggingface.co/datasets/OmniGen2/X2I2"><img src="https://img.shields.io/badge/Dataset-🤗-yellow" alt="model"></a>
</p> </p>
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## 🔥 News ## 🔥 News
- **2025-06-16**: [Gradio](https://github.com/VectorSpaceLab/OmniGen2?tab=readme-ov-file#-gradio-demo) and [Jupyter](https://github.com/VectorSpaceLab/OmniGen2/blob/main/example.ipynb) demo is available. - **2025-07-05**: Training datasets [X2I2](https://huggingface.co/datasets/OmniGen2/X2I2) are available.
- **2025-07-03**: OmniGen2 now supports [TeaCache](https://github.com/ali-vilab/TeaCache) and [TaylorSeer](https://github.com/Shenyi-Z/TaylorSeer) for faster inference, see [Usage Tips](#-usage-tips) for details. Thanks @legitnull for great [TeaCache-PR](https://github.com/VectorSpaceLab/OmniGen2/pull/52) and [TaylorSeer-PR](https://github.com/VectorSpaceLab/OmniGen2/pull/76).
- **2025-07-01**: OmniGen2 is supported by [ComfyUI official](https://comfyanonymous.github.io/ComfyUI_examples/omnigen), thanks !!
- **2025-06-30**: Training code is available, see [fine-tuning](docs/FINETUNE.md) for details.
- **2025-06-28**: We release [OmniContext](https://huggingface.co/datasets/OmniGen2/OmniContext) benchmark. The evaluation codes are in [omnicontext](https://github.com/VectorSpaceLab/OmniGen2/tree/main/omnicontext).
- **2025-06-24**: [Technical Report](https://arxiv.org/abs/2506.18871) is available.
- **2025-06-23**: We’ve updated our code and HF model—OmniGen2 now runs *without* `flash-attn`. Users can still install it for optimal performance.
- **2025-06-20**: Updated [resource requirements](#-resources-requirement), adding CPU offload support for devices with limited VRAM.
- **2025-06-16**: [Gradio](https://github.com/VectorSpaceLab/OmniGen2?tab=readme-ov-file#-gradio-demo) and [Jupyter](https://github.com/VectorSpaceLab/OmniGen2/blob/main/example.ipynb) is available. Online Gradio Demo: [Demo1](https://9c4426d27c3b9ecbed.gradio.live); [Chat-Demo1](https://0351497834a4d7226c.gradio.live); see more demo links in [gradio section](https://github.com/VectorSpaceLab/OmniGen2?tab=readme-ov-file#-gradio-demo)
- **2025-06-16**: We release **OmniGen2**, a multimodal generation model, model weights can be accessed in [huggingface](https://huggingface.co/OmniGen2/OmniGen2) and [modelscope](https://www.modelscope.cn/models/OmniGen2/OmniGen2). - **2025-06-16**: We release **OmniGen2**, a multimodal generation model, model weights can be accessed in [huggingface](https://huggingface.co/OmniGen2/OmniGen2) and [modelscope](https://www.modelscope.cn/models/OmniGen2/OmniGen2).
## 📌 TODO ## 📌 TODO
- [ ] Technical report. - [x] Technical report.
- [ ] In-context generation benchmark: **OmniContext**. - [x] Support CPU offload and improve inference efficiency.
- [ ] Support CPU offload and improve inference efficiency. - [x] In-context generation benchmark: **OmniContext**.
- [ ] Training data and scripts. - [ ] Integration of diffusers.
- [ ] Data construction pipeline. - [x] Training datasets.
- [ ] Training data construction pipeline.
- [ ] ComfyUI Demo (**commuity support will be greatly appreciated!**). - [ ] ComfyUI Demo (**commuity support will be greatly appreciated!**).
## 🚀 Quick Start ## 🚀 Quick Start