s a non-EMA variant, use the DiffusionPipeline.save_pretrained() method and specify the variant argument. You should try and save a variant to the same folder as the original checkpoint, so you can load both from the same folder:


	Copied
from diffusers import DiffusionPipeline

# save as fp16 variant
stable_diffusion.save_pretrained("runwayml/stable-diffusion-v1-5", variant="fp16")
# save as non-ema variant
stable_diffusion.save_pretrained("r