sses=1)
Once training is complete, take a look at the final 🦋 images 🦋 generated by your diffusion model!


	Copied
>>> import glob

>>> sample_images = sorted(glob.glob(f"{config.output_dir}/samples/*.png"))
>>> Image.open(sample_images[-1])


Next steps
	
Unconditional image generation is one example of a task that can be trained. You can explore other tasks and training techniques by visiting the 🧨 Diffusers Training Examples page. Here are 