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- # Midu-Stable-Diffusion-2-Chinese-Style-v0.1
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@@ -45,12 +45,23 @@ Training on 5M chinese style filtered data for 150k steps. Exponential moving av
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  ## Usage
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- 因为使用了customed tokenizer, 所以需要优先加载一下tokenizer
 
 
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  ```py
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- # !pip install git+https://github.com/huggingface/accelerate
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  import torch
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  from diffusers import StableDiffusionPipeline
 
 
 
 
 
 
 
 
 
 
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  ```
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+ # Chinese-Style-Stable-Diffusion-2-v0.1
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  ## Usage
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+ 因为使用了customed tokenizer, 所以需要优先加载一下tokenizer, 并传入trust_remote_code=True
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+
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+ Custom Tokenizer should be loaded first with 'trust_remote_code=True'.
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  ```py
 
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  import torch
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  from diffusers import StableDiffusionPipeline
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+ from transformers import AutoTokenizer
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+
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+ tokenizer_id = "lyua1225/clip-huge-zh-75k-steps-bs4096"
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+ sd2_id = "Midu/chinese-style-stable-diffusion-2-v0.1"
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+ tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, trust_remote_code=True)
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+ pipe = StableDiffusionPipeline.from_pretrained(sd2_id, torch_dtype=torch.float16, tokenizer=tokenizer)
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+ pipe.to("cuda")
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+
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+ image = pipe("赛博朋克风格的城市街道,8K分辨率,CG渲染", guidance_scale=10, num_inference_steps=20).images[0]
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+ image.save("cyberpunk.jpeg")
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  ```
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