---
license: other
---

# This is a Custom Diffusion model fine-tuned from the Stable Diffusion v1-4.

Custom Diffusion 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
```python
import os
import sys
import torch

os.system("git clone https://github.com/adobe-research/custom-diffusion")
sys.path.append("custom-diffusion")
from diffusers import StableDiffusionPipeline
from src import diffuser_training

device = 'cuda'
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to(self.device)

weight_path = 'custom_diffusion_cat.bin'
diffuser_training.load_model(pipe.text_encoder, pipe.tokenizer, pipe.unet, weight_path, '<new1>')
prompt = "<new1> cat swimming in a pool"
images = pipe(prompt, num_inference_steps=200, guidance_scale=6., eta=1.).images
```