Instructions to use inLine-XJY/ImVideoEdit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use inLine-XJY/ImVideoEdit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("inLine-XJY/ImVideoEdit", 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:
- 7e1ae77a3a3bcdb7a18b44e82e17034d4547fc79be4d2b7c733b4f435a96d98f
- Size of remote file:
- 1.4 kB
- SHA256:
- f3ff10977bd162742ec1620a13e50bcb506befa2fed30dbeaa91ce3d2a406d66
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