Image-to-Image
Diffusers
StableDiffusionInstructPix2PixPipeline
stable-diffusion
stable-diffusion-diffusers
art
Instructions to use instruction-tuning-sd/scratch-cartoonizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use instruction-tuning-sd/scratch-cartoonizer 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("instruction-tuning-sd/scratch-cartoonizer", 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:
- 47b101648a210321a21c6ad4a93e85a1419936ac833e5304d787b375e6fcb6a9
- Size of remote file:
- 3.44 GB
- SHA256:
- b83ec401685496c909d6d5d5be64ab3460d88f2f81906eb3b0c4b4561fb42362
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