pipe = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16)
+ pipe.enable_model_cpu_offload()
```  
4. By default, the text-to-image pipeline uses the [`DDIMScheduler`] but you can replace it with another scheduler like [`DDPMScheduler`] to see how that affects the tradeoff between inference speed and image quality:  
```py
from diffusers import DDPMScheduler
from diffusers import DiffusionPipeline