 in a bucket",
    num_inference_steps=100,
    guidance_scale=6.0,
    eta=1.0,
).images[0]
image.save("cat.png")
It’s possible to directly load these parameters from a Hub repository:


	Copied
import torch
from huggingface_hub.repocard import RepoCard
from diffusers import DiffusionPipeline

model_id = "sayakpaul/custom-diffusion-cat"
card = RepoCard.load(model_id)
base_model_id = card.data.to_dict()["base_model"]

pipe = DiffusionPipeline.f