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:
- 695e90c1cd9b64ad7abadcb2c9fcbe8877087810dd86628ce670b8bf8a2d81ab
- Size of remote file:
- 9.88 GB
- SHA256:
- 575c2dba750c3b40240fb742a4224453aa97dfbd3c5f5a0086be431cdefdd69c
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