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
Add diffusers-format transformer weights
#1
by YiYiXu HF Staff - opened
Adds the diffusers-format Wan-Animate-2 weights for huggingface/diffusers#14413:
transformer/: converted from the research state dict (conversion verified bitwise)scheduler/scheduler_config.json: the scheduler the release samples with (the current file saysUniPCMultistepScheduler, which does not matchmodel_index.json)modular_model_index.json: enablesModularPipeline.from_pretrainedon this repo; thetransformer/schedulerspecs pin this PR's revision so it is runnable before merging β they can be set tonullonce merged
kelseye changed pull request status to open
kelseye changed pull request status to merged