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README.md
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- dreambooth-hackathon
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- wildcard
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widget:
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- text:
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---
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# DreamBooth model for China-Chic-illustration trained by tilake aigc group on the own dataset.
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It can be used by modifying the `instance_prompt`: **style of \<guo-chao\> illustration**
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## Description
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This is a Stable Diffusion model fine-tuned on `China-Chic illustration` style images. It is trained by Tilake AIGC Group.
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If you like this model, click the \[❤ like\] button!
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## Examples
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- Prompt: ```a cute rabbit in red clothes, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/1.jpg">
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- Prompt: ```dragon dance, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/2.jpg">
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- Prompt: ```fireworks, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/3.jpg">
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- Prompt: ```a snowman, fireworks in the background, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/4.jpg">
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## Usage
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```python
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from diffusers import StableDiffusionPipeline
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pipeline = StableDiffusionPipeline.from_pretrained('tilake/China-Chic-illustration')
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image = pipeline("style of <guo-chao> illustration, a rabbit wearing sunglasses").images[0]
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image
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- dreambooth-hackathon
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- wildcard
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widget:
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- text: >-
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a rabbit wearing sunglasses, in the style of <guo-chao> illustration,
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trending on artstation, masterpiece, best quality
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language:
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- zh
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- en
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---
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# DreamBooth model for China-Chic-illustration
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This is the first model for `China-Chic illustration` (国潮插画) style painting. The model is based on Stable Diffusion model, fine-tuned the `China-Chic illustration` style taught to Stable Diffusion with DreamBooth. It is trained by tilake AIGC group on the own dataset.
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It can be used by modifying the `instance_prompt`: **style of \<guo-chao\> illustration**
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全球首个 “国潮插画” 风格定制化模型发布。该模型基于 Stable Diffusion model,并采用 DreamBooth 微调。该模型由 TiLake AIGC Group 在内部数据集上训练而来。
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你可以通过扩充以下 `instance_prompt` 来使用国潮插画模型绘制各种画作: **style of \<guo-chao\> illustration**
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## Description
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This is a Stable Diffusion model fine-tuned on `China-Chic illustration` style images. It is trained by Tilake AIGC Group.
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If you like this model, click the \[❤ like\] button!
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国潮插画是将传统文化和现代潮流审美进行结合的一种插画形式,开放该模型旨在给相关艺术家和工作者提供灵感和创作思路。如果喜欢该模型,欢迎点亮网页最上方的【like】按钮~
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## Examples
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- Prompt: ```a cute rabbit in red clothes, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality```(国潮兔)
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/1.jpg">
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- Prompt: ```dragon dance, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality```(国潮舞龙)
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/2.jpg">
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- Prompt: ```fireworks, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality```(国潮烟花)
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/3.jpg">
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- Prompt: ```a snowman, fireworks in the background, in the style of <guo-chao> illustration, trending on artstation, masterpiece, best quality```(国潮雪人)
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<img width="200px" height="200px" src="https://huggingface.co/tilake/China-Chic-illustration/resolve/main/example/4.jpg">
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## Usage
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```python
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from diffusers import StableDiffusionPipeline
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# guidance_scale=8.8 may be the best
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pipeline = StableDiffusionPipeline.from_pretrained('tilake/China-Chic-illustration')
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image = pipeline("style of <guo-chao> illustration, a rabbit wearing sunglasses").images[0]
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image
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