Image-to-Video
Diffusers
ONNX
video-generation
video diffusion transformer
audio-driven avatar animation
Instructions to use FrancisRing/FlashPortrait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FrancisRing/FlashPortrait 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("FrancisRing/FlashPortrait", 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
- Xet hash:
- 830d883ac0c31e060ca7da2b67d1c1d36c2fbb3ce93b35f6ce41d696baf065ef
- Size of remote file:
- 2.87 MB
- SHA256:
- 463aaa48dd24b9d3b966c76accf9a27f7c590a73a3827d5002a975e46bd54995
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