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  - en
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  ---
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  # yumekawa_diffusion
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- Generate a "Yumekawaii" image;
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- do not use too many Prompts.
 
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- Negative Prompt should be low quality, bad face, bad hands, etc.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Result
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  - en
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  ---
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  # yumekawa_diffusion
 
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+ [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1jUvv2RXEFo-fQVSSzVBs7vU22au3OLcC?usp=sharing#scrollTo=Ri6jRc9kAust)
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+ Generate a "Yumekawaii" image
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+ Do not use too many Prompts.
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+
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+ Negative Prompt should be low quality, bad face, bad hands, etc.
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+
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+
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+ <img src="https://s3.amazonaws.com/moonup/production/uploads/1673848269039-63056e2d99870e13d3df4e73.png" width="900" >
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+
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+ # How to run
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+
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+ You can run in Google colab[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1jUvv2RXEFo-fQVSSzVBs7vU22au3OLcC?usp=sharing#scrollTo=Ri6jRc9kAust)
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+
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+ Use [🤗HuggingFace Diffusers library](https://github.com/huggingface/diffusers)
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+
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+ clone the library
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+ ```
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+ pip install --upgrade git+https://github.com/huggingface/diffusers.git transformers accelerate scipy
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+ ```
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+ and run folowing scripts
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+
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+ ```python
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+ import torch
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+ from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
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+
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+ model_id = "teftef/yumekawa_diffusion_ver2.1"
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+
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+ scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
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+ pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler)
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+ pipe = pipe.to("cuda")
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+
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+ prompt = "a girl"
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+ negative_prompt="low quality,bad face,bad anatomy,bad hand"
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+ image = pipe(prompt,negative_prompt=negative_prompt).images[0]
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+
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+ image.save("output_img.png")
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+ ```
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  # Result
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