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README.md

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 license: apache-2.0
 library_name: transformers
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+<div align='center'>
+<h1>Emu3: Next-Token Prediction is All You Need</h1h1>
+<h3></h3>
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+[Emu3 Team, BAAI](https://www.baai.ac.cn/english.html)
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+| [Project Page](https://emu.baai.ac.cn) | [Paper](https://baai-solution.ks3-cn-beijing.ksyuncs.com/emu3/Emu3-tech-report.pdf?KSSAccessKeyId=AKLTgew6Kdg6RsK92QSfB2KLA&Expires=2591406552&Signature=6BvwfLVqvfww26Bhwvk3mG0FrL8%3D) | [🤗HF Models](https://huggingface.co/collections/BAAI/emu3-66f4e64f70850ff358a2e60f) | [github](https://github.com/baaivision/Emu3) |
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+</div>
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+<div align='center'>
+<img src="https://github.com/baaivision/Emu3/blob/main/assets/arch.png?raw=True" class="interpolation-image" alt="arch." height="80%" width="70%" />
+</div>
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+We introduce **Emu3**, a new suite of state-of-the-art multimodal models trained solely with **<i>next-token prediction</i>**! By tokenizing images, text, and videos into a discrete space, we train a single transformer from scratch on a mixture of multimodal sequences.
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+### Emu3 excels in both generation and perception
+**Emu3** outperforms several well-established task-specific models in both generation and perception tasks, surpassing flagship open models such as SDXL, LLaVA-1.6 and OpenSora-1.2, while eliminating the need for diffusion or compositional architectures.
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+<div align='center'>
+<img src="https://github.com/baaivision/Emu3/blob/main//assets/comparison.png?raw=True" class="interpolation-image" alt="comparison." height="80%" width="80%" />
+</div>
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+### Highlights
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+- **Emu3** is capable of generating high-quality images following the text input, by simply predicting the next vision token. The model naturally supports flexible resolutions and styles.
+- **Emu3** shows strong vision-language understanding capabilities to see the physical world and provides coherent text responses. Notably, this capability is achieved without depending on a CLIP and a pretrained LLM.
+- **Emu3** simply generates a video causally by predicting the next token in a video sequence, unlike the video diffusion model as in Sora. With a video in context, Emu3 can also naturally extend the video and predict what will happen next. 
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