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
Improve model card
#1
by nielsr HF Staff - opened
Hi! I'm Niels, part of the community science team at Hugging Face.
This PR improves the model card for HighSync by:
- Adding metadata tags for
library_nameandpipeline_tagto improve discoverability. - Linking the model to the original research paper on Arxiv and the official GitHub repository.
- Including installation and inference instructions from the GitHub repository to help users get started with the model.
saeed-5959 changed pull request status to merged