readme: ---
  tags:
  - hf_diffuse
  ---
  
  # Dummy diffusion model following architecture of https://github.com/lucidrains/denoising-diffusion-pytorch
  
  Run the model as follows:
  
  ```python
  from diffusers import UNetModel, GaussianDiffusion
  import torch
  
  # 1. Load model
  unet = UNetModel.from_pretrained("fusing/ddpm_dummy")
  
  # 2. Do one denoising step with model
  batch_size, num_channels, height, width = 1, 3, 32, 32
  dummy_noise = torch.ones((batch_size, num_channels, height, width))
  time_step = torch.tensor([10])
  image = unet(dummy_noise, time_step)
  
  # 3. Load sampler
  sampler = GaussianDiffusion.from_config("fusing/ddpm_dummy")
  
  # 4. Sample image from sampler passing the model
  image = sampler.sample(model, batch_size=1)
  
  print(image)
  ```