rsion(model_id, weight_name="<new2>.bin")

image = pipeline(
    "the <new1> cat sculpture in the style of a <new2> wooden pot",
    num_inference_steps=100,
    guidance_scale=6.0,
    eta=1.0,
).images[0]
image.save("multi-subject.png")
</hfoption>
</hfoptions>
 Next steps Congratulations on training a model with Custom Diffusion! 🎉 To learn more: Read the Multi-Concept Customization of Text-to-Image Diffusion blog post to learn more details 