Create README.md

README.md

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+<div align='center'>
+<h1>Emu: An Open Multimodal Generalist</h1h1>
+<h3><a href="">Generative Pretraining in Multimodality</a></h3>
+
+[Quan Sun](https://github.com/Quan-Sun)<sup>1*</sup>, [Qiying Yu](https://yqy2001.github.io)<sup>2,1*</sup>, [Yufeng Cui]()<sup>1*</sup>, [Fan Zhang]()<sup>1*</sup>, [Xiaosong Zhang](https://github.com/zhangxiaosong18)<sup>1*</sup>, [Yueze Wang]()<sup>1</sup>, [Hongcheng Gao]()<sup>1</sup>, [Jingjing Liu](https://air.tsinghua.edu.cn/en/info/1046/1194.htm)<sup>2</sup>, [Tiejun Huang](https://scholar.google.com/citations?user=knvEK4AAAAAJ&hl=en)<sup>1,3</sup>, [Xinlong Wang](https://www.xloong.wang/)<sup>1</sup>
+	
+<sup>1</sup> [BAAI](https://www.baai.ac.cn/english.html), <sup>2</sup> [THU](https://air.tsinghua.edu.cn), <sup>3</sup> [PKU](https://english.pku.edu.cn/) <br><sup>*</sup> Equal Contribution
+
+|  [Paper]() | [Demo(soon)]() |
+</div>
+
+**Emu** is a Large Multimodal Model (LMM) trained with a unified autoregressive objective, *i.e.*, predict-the-next-element, including both visual embeddings and textual tokens. Trained under this objective, **Emu** can serve as a generalist interface for diverse multimodal tasks, such as image captioning, image/video question answering, and text-to-image generation, together with new abilities like in-context text and image generation, and image blending.
+
+## Setup
+
+Clone the github repository and install required packages:
+
+```shell
+git clone https://github.com/baaivision/Emu
+cd Emu
+
+pip install -r requirements.txt
+```
+
+## Model Weights
+
+We release the pretrained and instruction-tuned weights of **Emu**. Our weights are subject to LLaMA's [license](https://github.com/facebookresearch/llama/blob/main/LICENSE).
+
+| Model name | Weight                                                  |
+| ---------- | ------------------------------------------------------- |
+| **Emu**    | [🤗 HF link](https://huggingface.co/BAAI/Emu/blob/main/Emu-pretrain.pt) (27GB) |
+| **Emu-I**  | [🤗 HF link](https://huggingface.co/BAAI/Emu/blob/main/Emu-instruct.pt) (27GB) |
+
+## Model Usage
+
+At present, we provide inference code for image captioning and visual question answering:
+
+```sh
+python emu_inference.py --instruct --ckpt-path $Instruct_CKPT_PATH
+```
+
+## Citation
+
+If you find Emu useful for your your research and applications, please consider citing:
+
+```
+@article{Emu,
+  title={Generative Pretraining in Multimodality},
+  author={Sun, Quan and Yu, Qiying and Cui, Yufeng and Zhang, Fan and Zhang, Xiaosong and Wang, Yueze and Gao, Hongcheng and Liu, Jingjing and Huang, Tiejun and Wang, Xinlong},
+  publisher={arXiv:},
+  year={2023},
+}
+