Image-to-Image
Diffusers
StableDiffusionInstructPix2PixPipeline
image-editing
instruct-pix2pix
magicbrush
Instructions to use JovanHengGhimHong/magicbrush-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JovanHengGhimHong/magicbrush-diffusers 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("JovanHengGhimHong/magicbrush-diffusers", 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
- Xet hash:
- 28e98252ec1e3b215e4933150b199dc87b9e74bf5e10aa636e4b42adb34ef9ce
- Size of remote file:
- 1.22 GB
- SHA256:
- a130277953b1f3a01e38407d98b79e43ebfad4310217a9d829644f838d61ed68
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.