>>> args = (config, model, noise_scheduler, optimizer, train_dataloader, lr_scheduler)

>>> notebook_launcher(train_loop, args, num_processes=1)
```  
Once training is complete, take a look at the final 🦋 images 🦋 generated by your diffusion model!  
```py
>>> import glob