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---
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- animal
widget:
- text: a photo of a zzelda cat in space
---
# DreamBooth model for the zzelda concept trained by Sanderbaduk on dataset of cats.
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.
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!
<table>
<tr>
<td>One of the images used to fine-tune on<br>"a photo of zzelda cat on a chair"</td>
<td>One of the images generated by the model<br>"a photo of zzelda cat in space"</td>
</tr>
<tr>
<td>
<img src="http://i.imgur.com/zFOzQtf.jpg" style="max-height:400px">
</td>
<td>
<img src="http://i.imgur.com/12Nilhg.png" style="max-height:400px">
</td>
</tr>
</table>
## Description
This is a Stable Diffusion model fine-tuned on images of my mum's cat Zelda for the animal theme.
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.
The model was trained on CPU after encountering issues with CUDA, taking around 2 hours on 32 cores.
It works a lot better locally than in the widget, where it tends to take a few more tries to get the right cat.
## Usage
```python
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('Sanderbaduk/zelda-the-cat')
image = pipeline().images[0]
image
```
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