





'''simple docstring'''






import torch

from diffusers import StableDiffusionPipeline


A__    :       Union[str, Any]              ='''path-to-your-trained-model'''
A__    :       Optional[int]              =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')

A__    :       Dict              ='''A photo of sks dog in a bucket'''
A__    :       int              =pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save('''dog-bucket.png''')













'''simple docstring'''






def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      if len(lowerCAmelCase  ) != len(lowerCAmelCase  ):
            raise ValueError("""String lengths must match!"""  )

      _lowerCAmelCase												=							0

      for chara, chara in zip(lowerCAmelCase							,     lowerCAmelCase  ):
            if chara != chara:
                  count += 1

      return count


if __name__ == "__main__":
      import doctest

      doctest.testmod()






