Image-to-Video
Diffusers
Safetensors
English
Chinese
WanVACEPipeline
video generation
video-to-video editing
refernce-to-video
Instructions to use kostakoff/Wan2.1-VACE-1.3B-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kostakoff/Wan2.1-VACE-1.3B-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kostakoff/Wan2.1-VACE-1.3B-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Download assets/logo.png from kostakoff/Wan2.1-VACE-1.3B-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 56.3 kB
-
https://huggingface.co/kostakoff/Wan2.1-VACE-1.3B-diffusers/resolve/main/assets/logo.png
- Command line
-
hf download hf://kostakoff/Wan2.1-VACE-1.3B-diffusers/assets/logo.png
-
curl -L -o logo.png https://huggingface.co/kostakoff/Wan2.1-VACE-1.3B-diffusers/resolve/main/assets/logo.png
56.3 kB
