ient_checkpointing \
  --max_train_steps=15000 \
  --learning_rate=1e-05 \
  --max_grad_norm=1 \
  --enable_xformers_memory_efficient_attention
  --lr_scheduler="constant" --lr_warmup_steps=0 \
  --output_dir="sd-pokemon-model" \
  --push_to_hub  Once training is complete, you can use your newly trained model for inference: PyTorch Flax    Copied from diffusers import StableDiffusionPipeline
import torch

pipeline = StableDiffusionPipeline.from