Instructions to use Wan-AI/Wan2.2-Animate-2-14B-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-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-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
Commit History
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Add diffusers-format transformer weights (#2)
- Add diffusers-format transformer weights (39bbd69d3353f9e7ddfc289f2dd53bef7dfa72ba) - Use DPMSolverMultistepScheduler (the scheduler the release samples with) (cde15a5e2e01c31cab5c23c856bcb72597056fe7) - Add modular_model_index.json for ModularPipeline.from_pretrained (0f530913f868144adc0184e8612f23bfed130458) Co-authored-by: YiYi Xu <YiYiXu@users.noreply.huggingface.co>7d48412