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--- |
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license: mit |
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tags: |
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- pytorch |
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- diffusers |
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- unconditional-image-generation |
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- diffusion-models-class |
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datasets: |
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- mnist |
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library_name: diffusers |
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pipeline_tag: unconditional-image-generation |
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thumbnail: https://upload.wikimedia.org/wikipedia/commons/f/f7/MnistExamplesModified.png |
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--- |
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# Unconditional MNIST DDPM |
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## Description |
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This model is a very lightweight UNet2D trained on the MNIST dataset. \ |
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This model is unconditional, meaning that you cannot pick which number you'd like to generate. \ |
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This model was trained in ~40min on an L4 GPU Google Colab instance. You can see the training logs in the [Training metrics](https://huggingface.co/1aurent/ddpm-mnist/tensorboard) tab. |
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A conditional model is available at [1aurent/ddpm-mnist-conditional](https://huggingface.co/1aurent/ddpm-mnist-conditional), though it is pretty buggy. |
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## Usage |
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```python |
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from diffusers import DDPMPipeline |
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pipeline = DDPMPipeline.from_pretrained('1aurent/ddpm-mnist') |
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image = pipeline().images[0] |
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image |
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``` |
