Instructions to use ByteDance/LatentSync with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/LatentSync with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/LatentSync", 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:
- 829a45a3d1d8cc868584bdd6a8f95f2c166fe9c25ac53c926925f8a0799a3149
- Size of remote file:
- 1.49 GB
- SHA256:
- 38fa63bad3ed2332f647c40a5dc616cb0e233db8579f698f62af4c41965c4da5
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