```  
That's pretty much it! Aside from the differences described here, the rest of the script is very similar to the [Text-to-image](text2image#training-script) training script, so feel free to check it out for more details. If you want to learn more about how the training loop works, check out the [Understanding pipelines, models and schedulers](../using-diffusers/write_own_pipeline) tutorial which breaks down the basic pattern of the denoising process.