random seed is taken every time, thus leading to a different result.
This is a desired property of diffusion pipelines, as it means that the pipeline can create a different random image every time it is run. In many cases, one would like to generate the exact same image of a certain
run, for which case an instance of a PyTorch generator has to be passed:


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import torch
from diffusers import DDIMPipeline
import numpy as np

model_id = "g