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
git clone https://github.com/adobe-research/custom-diffusion
cd custom-diffusion
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
- Downloads last month
- 16
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no pipeline_tag.