

lowerCAmelCase							:  Any            =						'\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

lowerCAmelCase							:  List[Any]            =						[{'type': 'code', 'content': INSTALL_CONTENT}]
lowerCAmelCase							:  Union[str, Any]            =						{
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}









import torch

from diffusers import StableDiffusionPipeline


lowerCAmelCase							:  Any            =						"""path-to-your-trained-model"""
lowerCAmelCase							:  int            =						StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")

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

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






