m_class_images=200 \
  --scale_lr \
  --hflip  \
  --modifier_token "<new1>+<new2>" \
  --push_to_hub
</hfoption>
</hfoptions>
Once training is finished, you can use your new Custom Diffusion model for inference.
<hfoptions id="training-inference">
<hfoption id="single concept">

	  Copied import torch
from diffusers import DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(
    "CompVis/stable-diffusion-v1-4", torch_dtype=torch.fl