Instructions to use fal/Wan2.1-VACE-14B-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/Wan2.1-VACE-14B-FlashPack with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/Wan2.1-VACE-14B-FlashPack", 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:
- dd8da44e902b69cbee5073ab6b91f8d879262cbce3ba946d1a0f49bce005abc0
- Size of remote file:
- 34.7 GB
- SHA256:
- 6a3089a50c7f1a85eac140ff9af459e7f84ad32f60f2184b9cd6eb0f69e13af6
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