Instructions to use huaichang/PersonaLive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use huaichang/PersonaLive 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("huaichang/PersonaLive", 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
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<sup>1</sup> University of Macau <sup>2</sup> [Dzine.ai](https://www.dzine.ai/) <sup>3</sup> [GVC Lab, Great Bay University](https://gvclab.github.io/)
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<sup>1</sup> University of Macau <sup>2</sup> [Dzine.ai](https://www.dzine.ai/) <sup>3</sup> [GVC Lab, Great Bay University](https://gvclab.github.io/)
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⚡️ Real-time, Streamable, Infinite-Length Portrait Animation requires only ~12GB VRAM ⚡️
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