--output_dir="ddpm-ema-flowers-64" \
--mixed_precision="fp16" \
--push_to_hub
```  
</hfoption>
</hfoptions>  
The training script creates and saves a checkpoint file in your repository. Now you can load and use your trained model for inference:  
```py
from diffusers import DiffusionPipeline
import torch