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--- |
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license: creativeml-openrail-m |
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tags: |
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- pytorch |
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- diffusers |
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- stable-diffusion |
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- text-to-image |
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- diffusion-models-class |
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- dreambooth-hackathon |
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- animal |
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widget: |
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- text: a photo of a zzelda cat in space |
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--- |
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# DreamBooth model for the zzelda concept trained by Sanderbaduk on dataset of cats. |
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This is a Stable Diffusion model fine-tuned on pictures of my mum's cat "Zelda" with DreamBooth. It can be used by using the phrase 'zzelda cat' in a prompt. |
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This model was created as part of the DreamBooth Hackathon 🔥. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part! |
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<table> |
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<tr> |
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<td>One of the images used to fine-tune on<br>"a photo of zzelda cat on a chair"</td> |
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<td>One of the images generated by the model<br>"a photo of zzelda cat in space"</td> |
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</tr> |
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<tr> |
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<td> |
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<img src="http://i.imgur.com/zFOzQtf.jpg" style="max-height:400px"> |
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</td> |
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<td> |
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<img src="http://i.imgur.com/12Nilhg.png" style="max-height:400px"> |
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</td> |
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</tr> |
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</table> |
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## Description |
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This is a Stable Diffusion model fine-tuned on images of my mum's cat Zelda for the animal theme. |
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To experiment a bit, I used a custom prompt for each image based on the file name. This works, but does not seem to have made much of a difference. |
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The model was trained on CPU after encountering issues with CUDA, taking around 2 hours on 32 cores. |
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It works a lot better locally than in the widget, where it tends to take a few more tries to get the right cat. |
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## Usage |
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```python |
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from diffusers import StableDiffusionPipeline |
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pipeline = StableDiffusionPipeline.from_pretrained('Sanderbaduk/zelda-the-cat') |
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image = pipeline().images[0] |
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image |
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``` |
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