Instructions to use ApacheOne/Wan2.2-Animate-2-14B-OrbitQuant-W4A4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ApacheOne/Wan2.2-Animate-2-14B-OrbitQuant-W4A4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ApacheOne/Wan2.2-Animate-2-14B-OrbitQuant-W4A4", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
File size: 596 Bytes
f2c0505 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"package": "OrbitQuant_WanAnimate2_FreshColab_W4A4_v3",
"build_host": {
"python": "3.13.5",
"platform": "Linux-6.18.35-x86_64-with-glibc2.41"
},
"compileall": "PASS",
"pytest": {
"status": "PASS",
"tests": 17
},
"gpu_validation_on_build_host": "NOT_AVAILABLE",
"mandatory_colab_gates": [
"CUDA available and SM80+",
"Torch>=2.10",
"CUDA>=12.8",
"Triton>=3.6",
"A4 parity d=5120",
"A4 parity d=13824",
"packed W4A4 parity real shapes",
"actual packed artifact matrix gate",
"480 packed modules",
"480 active modules"
]
}
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