Instructions to use linoyts/Wan-VACE-14B-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use linoyts/Wan-VACE-14B-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("linoyts/Wan-VACE-14B-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c33ed693a6e9efae078a514b174bca17902d8022df61656b3052828afe6bac7d
- Size of remote file:
- 4.95 GB
- SHA256:
- 9065eb4c5b57536a85d77815e887c7e9a7ffd295c97e47e9176ceebd75989907
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.