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:
- 48c57cca11fece23b9033f7320a0722043403e7295313a4867eec256e084c231
- Size of remote file:
- 3.96 GB
- SHA256:
- 7a1e460a08dff6eb43b64bb20cb05309c1d34920177acb17a1cef8311dd4dd42
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