Instructions to use Wan-AI/Wan2.2-Animate-2-14B-Distilled-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.2-Animate-2-14B-Distilled-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("Wan-AI/Wan2.2-Animate-2-14B-Distilled-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
Wan2.2-Animate-2-14B-Distilled-Diffusers / transformer /diffusion_pytorch_model-00003-of-00004.safetensors
- Xet hash:
- 84fe5dc7f62403478759f41b311081e57798fe738ee9e936ae6d2d1b8e5d8d29
- Size of remote file:
- 9.95 GB
- SHA256:
- 444eeea631fe6d2df80780f521f6c7716bd079fc177279ba09d2d20479f2dfaf
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