Instructions to use FastVideo/HY-WorldPlay-AR-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FastVideo/HY-WorldPlay-AR-Diffusers 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("FastVideo/HY-WorldPlay-AR-Diffusers", 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:
- c9f677e043e5598787798939b95f9cefd82a05d7eabd1bef2dc544587f0b6358
- Size of remote file:
- 877 MB
- SHA256:
- 3f3b22f7926015b76022ca4842a3130d83c477d4ecee8a5275252650d96bf97a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.