| --- |
| language: |
| - en |
| license: apache-2.0 |
| library_name: diffusers |
| tags: |
| - diffusion |
| datasets: |
| - huggan/smithsonian_butterflies_subset |
| --- |
| # Model Card for Smithsonian128UNet |
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| <!-- Provide a quick summary of what the model is/does. --> |
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| A pre-trained ControlNet on the Smithsonain Butterflies 128x128 dataset (HuggingFace) using Canny images as conditioning. |
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| ### Model Description |
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| An EMA model saved at the conclusion of training (1000 epochs) of an unconditional diffusion model on the Smithsonian Butterflies 128x128 dataset. Trained using the Simple Diffusion paradigm |
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| - **Developed by:** [Gian Favero] |
| - **License:** [Apache 2.0] |
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| ### Model Sources [optional] |
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| <!-- Provide the basic links for the model. --> |
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| - **Repository:** [https://github.com/faverogian/simpleDiffusion] |
| - **Paper [optional]:** [https://arxiv.org/pdf/2301.11093] |
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| ## How to Get Started with the Model |
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| Full usage details can be found at the GitHub repository page. |
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| ## Environmental Impact |
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| <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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| Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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| - **Hardware Type:** 4x 16GB V100 |
| - **Hours used:** 1 hour |
| - **Compute Region:** Canada |
