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:
- 6c229ac224c9cb42e07c6252c0c574b54be92b04c7d024c6a4fd3fbf58f7d2d7
- Size of remote file:
- 263 MB
- SHA256:
- 0fef72cdb5e98df1624e374ea4f824f033a805e3a7fa413ed036a5c8ac0f9266
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