teps=1 --gradient_checkpointing \
  --learning_rate=5e-6 \
  --lr_scheduler="constant" \
  --lr_warmup_steps=0 \
  --num_class_images=200 \
  --max_train_steps=800 \
  --mixed_precision=fp16

Inference
	
Once you have trained a model, inference can be done using the StableDiffusionPipeline, by simply indicating the path where the model was saved. Make sure that your prompts include the special identifier used during training (sks in the previou