Instructions to use thucdangvan020999/lip_sync with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thucdangvan020999/lip_sync with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("thucdangvan020999/lip_sync", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd7042cdab72e6557bcd9861cbc4b9530281d858fe5d77366e6108a5ef6daa1d
- Size of remote file:
- 3.4 GB
- SHA256:
- 0ee7d5ea03ea75d8dca50ea7a76df791e90633687a135c4a69393abfc0475ffe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.