Image-to-Image
Diffusers
ONNX
Safetensors
StableDiffusionXLInpaintPipeline
stable-diffusion-xl
inpainting
virtual try-on
Instructions to use efdev/IDM-VTON with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use efdev/IDM-VTON 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("efdev/IDM-VTON", 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:
- d76dfd1ddb8aa2401614b7c842674f841453e13dbba7bc693a9541e4ce7fd231
- Size of remote file:
- 256 MB
- SHA256:
- b8a7382001b16e453bad95ca9dbc68ae8f2b839b304cf90eaf5c27fbdb4dae91
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