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---
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license: mit
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license_name: deepseek
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license_link: LICENSE
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pipeline_tag: any-to-any
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library_name: transformers
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tags:
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- muiltimodal
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- text-to-image
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- unified-model
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---
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## 1. Introduction
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Janus-Pro is a novel autoregressive framework that unifies multimodal understanding and generation.
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It addresses the limitations of previous approaches by decoupling visual encoding into separate pathways, while still utilizing a single, unified transformer architecture for processing. The decoupling not only alleviates the conflict between the visual encoder’s roles in understanding and generation, but also enhances the framework’s flexibility.
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Janus surpasses previous unified model and matches or exceeds the performance of task-specific models.
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The simplicity, high flexibility, and effectiveness of Janus make it a strong candidate for next-generation unified multimodal models.
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[**Github Repository**](https://github.com/deepseek-ai/Janus)
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<div align="center">
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<img alt="image" src="janus_pro_teaser1.png" style="width:90%;">
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</div>
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<div align="center">
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<img alt="image" src="janus_pro_teaser2.png" style="width:90%;">
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</div>
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### 2. Model Summary
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Janus-Pro is a unified understanding and generation MLLM, which decouples visual encoding for multimodal understanding and generation.
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Janus is constructed based on the DeepSeek-LLM-1.5b-base/DeepSeek-LLM-7b-base.
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For multimodal understanding, it uses the [SigLIP-L](https://huggingface.co/timm/ViT-L-16-SigLIP-384) as the vision encoder, which supports 384 x 384 image input. For image generation, Janus uses the tokenizer from [here](https://github.com/FoundationVision/LlamaGen) with a downsample rate of 16.
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## 3. Quick Start
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Please refer to [**Github Repository**](https://github.com/deepseek-ai/Janus)
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## 4. License
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This code repository is licensed under [the MIT License](https://github.com/deepseek-ai/DeepSeek-LLM/blob/HEAD/LICENSE-CODE). The use of Janus models is subject to [DeepSeek Model License](https://github.com/deepseek-ai/DeepSeek-LLM/blob/HEAD/LICENSE-MODEL).
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## 5. Citation
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```
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@misc{chen2025januspro,
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title={Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling},
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author={Xiaokang Chen and Zhiyu Wu and Xingchao Liu and Zizheng Pan and Wen Liu and Zhenda Xie and Xingkai Yu and Chong Ruan},
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year={2025},
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}
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```
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## 6. Contact
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If you have any questions, please raise an issue or contact us at [[email protected]](mailto:[email protected]). |
