cause that is where the bulk of the computation is done. Here are some tips to improve Kandinsky during inference. Enable xFormers if you’re using PyTorch < 2.0:   Copied   from diffusers import DiffusionPipeline
  import torch

  pipe = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16)
+ pipe.enable_xformers_memory_efficient_attention() Enable torch.compile if you’re using PyTorch >= 2.0 to autom