Image-to-Image
Diffusers
StableDiffusionInstructPix2PixPipeline
stable-diffusion
stable-diffusion-diffusers
art
Instructions to use AnalogMutations/cartoonizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AnalogMutations/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("AnalogMutations/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
Download unet/diffusion_pytorch_model.bin from AnalogMutations/cartoonizer: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/AnalogMutations/cartoonizer/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://AnalogMutations/cartoonizer/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/AnalogMutations/cartoonizer/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- ef474024a08e7a25a76c5aa4945a1a5c8e55776790d699a8bf7e20527a68f331
- Size of remote file:
- 3.44 GB
- SHA256:
- e9b6afa263fe85a2f7408a51b9d3052351a18f8eb86e8c364eb542bfe2161d7d
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