readme: ---
  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
  ```
  