Image-to-Video
Diffusers
Safetensors
English
Chinese
vace
video generation
video-to-video editing
refernce-to-video
Instructions to use Wan-AI/Wan2.1-VACE-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-VACE-14B 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("Wan-AI/Wan2.1-VACE-14B", 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
VACE + 3D stereo camera option - new feature idea
#9
by MavenDE - opened
Hello!
Best model yet!
Would be awesome if in the next version or a modification of VACE you could let us have different camera views of the same exact rendering.
I am thinking about 3D stereo rendering for VR. Just imagine if you could setup VACE to render something and through extra node get the other eye's view of the scene, make a high quality 3D video of the scene, also in VR180.
Cheers!
Would training the model on VR images work? I've seen other (image) models do it on civit.
which ones?