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README.md
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- StyleTransfer
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- QwenImageEdit
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# QwenStyle: Content-Preserving Style Transfer with Qwen-Image-Edit
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For the first time, we introduce Content-Preserving Style Transfer functionality to Qwen-Image-Edit, which supports transferring various style cues from style reference to content reference while preserving the characteristics of content reference in high efficiency, i.e. 4 sampling steps.
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Please note that our style transfer model is based on Qwen-Image-Edit-2509, and has to be used with Qwen-Image-Lightning Lora, which we have converted to Diffsynth format for compatibility. Otherwise, the model may suffer from either low-speed or low-quality.
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## Quick Start
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pip install -e .
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```
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Then run infer_style_transfer.py for inference. We have tested the model on one H100, which takes 5 seconds to generate the result.
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## Training
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Our training framework is based on DiffSynth-Studio. Special thanks to the authors of DiffSynth.
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## Data
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We will
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## Citation
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We
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```bibtex
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@article{zhang2026qwenstyle,
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journal={TeleAI},
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year={2026}
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}
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```
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- StyleTransfer
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- QwenImageEdit
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---
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# QwenStyle: Content-Preserving Style Transfer with Qwen-Image-Edit
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For the first time, we introduce Content-Preserving Style Transfer functionality to Qwen-Image-Edit, which supports transferring various style cues from style reference to content reference while preserving the characteristics of content reference in high efficiency, i.e. 4 sampling steps.
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Please note that our style transfer model is based on [Qwen-Image-Edit-2509](https://huggingface.co/Qwen/Qwen-Image-Edit-2509), and has to be used with [Qwen-Image-Lightning Lora](https://huggingface.co/lightx2v/Qwen-Image-Lightning), which we have converted to Diffsynth format for compatibility. Otherwise, the model may suffer from either low-speed or low-quality.
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Our github page is [QwenStyle](https://github.com/witcherofresearch/Qwen-Image-Style-Transfer).
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## Quick Start
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pip install -e .
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```
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Please download our style transfer lora and lightning lora from [this link](https://huggingface.co/witcherderivia/Qwen-Image-Style-Transfer/)
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Then run infer_style_transfer.py for inference. We have tested the model on one H100, which takes 5 seconds to generate the result.
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## Training
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Our training framework is based on [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio). Special thanks to the authors of DiffSynth.
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## Data
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We will open-source all our training data if the stars exceed 200.
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## Citation
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We release the tech report of [QwenStyle V1](https://openreview.net/forum?id=Cgb7JpOA5Q&referrer=%5Bthe%20profile%20of%20Shiwen%20Zhang%5D(%2Fprofile%3Fid%3D~Shiwen_Zhang1)). We are keep refining QwenStyle and will update new versions in the future. Please light a star for our project and cite our work if you find it helpful.
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```bibtex
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@article{zhang2026qwenstyle,
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journal={TeleAI},
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year={2026}
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}
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```
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