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@@ -33,7 +33,7 @@ We believe that a well-developed open-source code framework can lower the thresh
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> Currently, the development personnel of this project are limited, with most of the work handled by [Artiprocher](https://github.com/Artiprocher). Therefore, the progress of new feature development will be relatively slow, and the speed of responding to and resolving issues is limited. We apologize for this and ask developers to understand.
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- **January 12, 2026**: We trained and open-sourced a text-guided image layer separation model ([Model Link](https://modelscope.cn/models/DiffSynth-Studio/Qwen-Image-Layered-Control)). Given an input image and a textual description, the model isolates the image layer corresponding to the described content.
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- **January 12, 2026**: We trained and open-sourced a text-guided image layer separation model ([Model Link](https://modelscope.cn/models/DiffSynth-Studio/Qwen-Image-Layered-Control)). Given an input image and a textual description, the model isolates the image layer corresponding to the described content. For more details, please refer to our blog post ([Chinese version](https://modelscope.cn/learn/4938), [English version](https://huggingface.co/blog/kelseye/qwen-image-layered-control)).
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- **December 24, 2025**: Based on Qwen-Image-Edit-2511, we trained an In-Context Editing LoRA model ([Model Link](https://modelscope.cn/models/DiffSynth-Studio/Qwen-Image-Edit-2511-ICEdit-LoRA)). This model takes three images as input (Image A, Image B, and Image C), and automatically analyzes the transformation from Image A to Image B, then applies the same transformation to Image C to generate Image D. For more details, please refer to our blog post ([Chinese version](https://mp.weixin.qq.com/s/41aEiN3lXKGCJs1-we4Q2g), [English version](https://huggingface.co/blog/kelseye/qwen-image-edit-2511-icedit-lora)).
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