Image-to-Image
Diffusers
StableDiffusionInpaintPipeline
stable-diffusion
stable-diffusion-diffusers
text-guided-to-image-inpainting
endpoints-template
Instructions to use philschmid/stable-diffusion-2-inpainting-endpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use philschmid/stable-diffusion-2-inpainting-endpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("philschmid/stable-diffusion-2-inpainting-endpoint", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3 opened 6 months ago
by
SFconvertbot
Add `scale_factor` to vae config.
#1 opened over 3 years ago
by
valhalla