Instructions to use saeed-5959/high_sync with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use saeed-5959/high_sync 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("saeed-5959/high_sync", 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:
- 0abc84f11f77863473ee4446d4ba022c323912d4eeb5795ea89b672992bd19f5
- Size of remote file:
- 113 kB
- SHA256:
- 87b8a0583e481839a98d27068370979b36a6e2bc95aa79ffeeb89cd324d47bb6
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