Instructions to use ferdap/Wan2.2-Animate-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ferdap/Wan2.2-Animate-14B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ferdap/Wan2.2-Animate-14B", 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:
- 0f8429a1c06bd6bbeacfa4ceb5240f83161297086cd5eb29fb5d1646f7892785
- Size of remote file:
- 9.98 GB
- SHA256:
- b90b820627d43eeeb1ae0489182f9a8c870374fd72cc99dccb9eddfc2ace8325
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