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
Commit History
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Add diffusers-format transformer weights (#1)
- Add diffusers-format transformer weights (8543b2c5f79be17b4eb16a71c603b1389bbc31e0) - Use FlowMatchEulerDiscreteScheduler (the scheduler the release samples with) (aefb15dae2887ffeffa93a0de3a8ba4df6b22a7d) - Point the scheduler entry at the class the config holds (001325dc57488c02f01c88e300b441462398a4b4) - Add modular_model_index.json for ModularPipeline.from_pretrained (ff28d41a9c0c331137691847cc8700593d785593) Co-authored-by: YiYi Xu <YiYiXu@users.noreply.huggingface.co>59e4141
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initial commit
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