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-00002-of-00004.safetensors
- Xet hash:
- fc0b87326f14ef9ae2be2f560cb52327030240359263c297f1dd029f7e2bc8b6
- Size of remote file:
- 9.98 GB
- SHA256:
- e808cf7a7e7aaf358478a2198152f9e3ec8609c66712be397c21b4b7ec7ef501
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