

import torch

from diffusers import StableDiffusionPipeline


a_    :						int    		=      "path-to-your-trained-model"
a_    :						List[str]    		=      StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("cuda")

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

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




def        __lowerCAmelCase    (       _UpperCamelCase		:  str		,							_UpperCamelCase		:  int	)		->							list[str]:
 '''simple docstring'''


 return [sentence[i : i + ngram_size] for i in range(len(_UpperCamelCase	) - ngram_size + 1	)]


if __name__ == "__main__":
      from doctest import testmod

      testmod()

