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