How to use intel-ai/Wan2.2-Animate-14B-Diffusers-MXFP8-AutoRound 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("intel-ai/Wan2.2-Animate-14B-Diffusers-MXFP8-AutoRound", 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")
How to use intel-ai/Wan2.2-Animate-14B-Diffusers-MXFP8-AutoRound with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
https://huggingface.co/intel-ai/Wan2.2-Animate-14B-Diffusers-MXFP8-AutoRound/resolve/main/examples/__pycache__/run_example.cpython-312.pyc
hf download hf://intel-ai/Wan2.2-Animate-14B-Diffusers-MXFP8-AutoRound/examples/__pycache__/run_example.cpython-312.pyc
curl -L -o run_example.cpython-312.pyc https://huggingface.co/intel-ai/Wan2.2-Animate-14B-Diffusers-MXFP8-AutoRound/resolve/main/examples/__pycache__/run_example.cpython-312.pyc
