readme: ---
  license: other
  tags:
    - pytorch
    - stable-diffusion
    - stable-diffusion-diffusers
    - diffusers
  ---
  
  # This is a Custom Diffusion model fine-tuned from the Stable Diffusion v1-4.
  
  [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion/index.html) allows you to fine-tune text-to-image diffusion models, such as Stable Diffusion, given a few images of a new concept (~4-20). 
  
  Here we give an example model fine-tuned using 5 images of a cat downloaded from UnSplash. The example code of inference is shown below.
  
  
  ## Example code of inference
  ```
  git clone https://github.com/adobe-research/custom-diffusion
  cd custom-diffusion
  
  ```
  ```python
  from diffusers import StableDiffusionPipeline
  from src import diffuser_training
  
  device = 'cuda'
  model_id = "CompVis/stable-diffusion-v1-4"
  pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
  pipe = pipe.to(device)
  
  diffuser_training.load_model(pipe.text_encoder, pipe.tokenizer, pipe.unet, 'cat.bin')
  
  prompt = "<new1> cat swimming in a pool"
  images = pipe(prompt, num_inference_steps=200, guidance_scale=6., eta=1.).images
  ```
  
  <center>
  <img src="https://huggingface.co/custom-diffusion-library/cat/resolve/main/cat.png" width="600" align="center" >
  </center>
  
  