readme: ---
  license: mit
  ---
  ### abstract_patterns_in_nature on Stable Diffusion via Dreambooth trained on the [fast-DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
  #### model by apurik-parv
  This your the Stable Diffusion model fine-tuned the abstract_patterns_in_nature concept taught to Stable Diffusion with Dreambooth.
  It can be used by modifying the `instance_prompt(s)`: **abnapa**
  #### This is an attempt to teach symmetry and its scales to stable diffusion model. This first version was trained on abstract patterns from nature and it markedly produces different images from the original model sometime better sometimes no so better or even worse at times it even seems to correct the lighting and shadows. Users please give your comments after usage so that we can really understand what this model does.
  You can also train your own concepts and upload them to the library by using [the fast-DremaBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb).
  And you can run your new concept via `diffusers`: [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb), [Spaces with the Public Concepts loaded](https://huggingface.co/spaces/sd-dreambooth-library/stable-diffusion-dreambooth-concepts)