 num_inference_steps=50,
    cross_attention_guidance_amount=0.15,
).images
images[0].save("edited_image_dog.png")

Based on an input image
	
When the pipeline is conditioned on an input image, we first obtain an inverted
noise from it using a DDIMInverseScheduler with the help of a generated caption. Then
the inverted noise is used to start the generation process. 
First, let’s load our pipeline: 


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import torch
from transformers impor