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
Add video-to-video pipeline tag
Browse files
README.md
CHANGED
|
@@ -3,6 +3,7 @@ license: openrail++
|
|
| 3 |
library_name: diffusers
|
| 4 |
tags:
|
| 5 |
- video-to-video
|
|
|
|
| 6 |
---
|
| 7 |
|
| 8 |
# The checkpoints of LatentSync
|
|
|
|
| 3 |
library_name: diffusers
|
| 4 |
tags:
|
| 5 |
- video-to-video
|
| 6 |
+
pipeline_tag: video-to-video
|
| 7 |
---
|
| 8 |
|
| 9 |
# The checkpoints of LatentSync
|