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README.md
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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-Pro 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. Usage Examples
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### Single Image Inference
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image.save(f"image{i}.png")
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```
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##
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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-Pro models is subject to [DeepSeek Model License](https://github.com/deepseek-ai/DeepSeek-LLM/blob/HEAD/LICENSE-MODEL).
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##
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```
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@article{chen2025janus,
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}
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```
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##
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If you have any questions, please raise an issue or contact us at [[email protected]](mailto:[email protected]).
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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-Pro uses the tokenizer from [here](https://github.com/FoundationVision/LlamaGen) with a downsample rate of 16.
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## 3. Usage Examples
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### Single Image Inference
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image.save(f"image{i}.png")
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```
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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-Pro 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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@article{chen2025janus,
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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]).
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