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目前的开源 Diffusion 模型结构五花八门,以文生图模型为例,有 Stable Diffusion、Kolors、FLUX 等。
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|FLUX|Stable Diffusion 3|Kolors|Hunyuan-DiT|Stable Diffusion|Stable Diffusion XL|
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| FLUX | Stable Diffusion 3 | Kolors | Hunyuan-DiT | Stable Diffusion | Stable Diffusion XL |
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| <img src="https://github.com/user-attachments/assets/984561e9-553d-4952-9443-79ce144f379f" width="80"/> | <img src="https://github.com/modelscope/DiffSynth-Studio/assets/35051019/4df346db-6f91-420a-b4c1-26e205376098" width="80"/> | <img src="https://github.com/modelscope/DiffSynth-Studio/assets/35051019/53ef6f41-da11-4701-8665-9f64392607bf" width="80"/> | <img src="https://github.com/modelscope/DiffSynth-Studio/assets/35051019/60b022c8-df3f-4541-95ab-bf39f2fa8bb5" width="80"/> | <img src="https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/6fc84611-8da6-4a1f-8fee-9a34eba3b4a5" width="80"/> | <img src="https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/67687748-e738-438c-aee5-96096f09ac90" width="80"/> |
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我们设计了统一的框架,实现了通用的增强模块,例如提示词分区控制技术。
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|Without LoRA|||||
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|With LoRA|||||
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||FLUX.1-dev|Kolors|Stable Diffusion 3|Hunyuan-DiT|
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|Without LoRA|<img src="https://github.com/user-attachments/assets/df62cef6-d54f-4e3d-a602-5dd290079d49" width="100" alt="image_without_lora">|<img src="https://github.com/modelscope/DiffSynth-Studio/assets/35051019/9d79ed7a-e8cf-4d98-800a-f182809db318" width="100" alt="image_without_lora">|<img src="https://github.com/modelscope/DiffSynth-Studio/assets/35051019/ddb834a5-6366-412b-93dc-6d957230d66e" width="100" alt="image_without_lora">|<img src="https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/1aa21de5-a992-4b66-b14f-caa44e08876e" width="100" alt="image_without_lora">|
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|With LoRA|<img src="https://github.com/user-attachments/assets/4fd39890-0291-4d19-8a88-d70d0ae18533" width="100" alt="image_with_lora">|<img src="https://github.com/modelscope/DiffSynth-Studio/assets/35051019/02f62323-6ee5-4788-97a1-549732dbe4f0" width="100" alt="image_with_lora">|<img src="https://github.com/modelscope/DiffSynth-Studio/assets/35051019/8e7b2888-d874-4da4-a75b-11b6b214b9bf" width="100" alt="image_with_lora">|<img src="https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/83a0a41a-691f-4610-8e7b-d8e17c50a282" width="100" alt="image_with_lora">|
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## 互联
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与语言模型不同,Diffusion 模型存在生态模型,包括 LoRA、ControlNet、IP-Adapter 等,这些模型由不同的开发者开发、训练、开源,我们为这些模型提供了一站式的推理支持。例如基于 Stable Diffusion XL,你可以随意使用这些相关的生态模型组装出丰富的功能。
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|底模生成|使用 ControlNet 保持画面结构重新生成|继续叠加 LoRA 使画面更扁平|叠加 IP-Adapter 转换为水墨风格|
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|<img src="https://github.com/user-attachments/assets/cc094e8f-ff6a-4f9e-ba05-7a5c2e0e609f" width="100" >|<img src="https://github.com/user-attachments/assets/d50d173e-e81a-4d7e-93e3-b2787d69953e" width="100" >|<img src="https://github.com/user-attachments/assets/c599b2f8-8351-4be5-a6ae-8380889cb9d8" width="100" >|<img src="https://github.com/user-attachments/assets/e5924aef-03b0-4462-811f-a60e2523fd7f" width="100" >|
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你甚至可以继续叠加 AnimateDiff 构建视频转绘方案。
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