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:
- a58926bfffbcde7c28b8697e943bc1ab2522e34bba023f1e2cf97e00f4404aef
- Size of remote file:
- 222 MB
- SHA256:
- 15a76819cdf98f4fe587a705777ff03408c0b049bdb791c24dd1eea83fb11072
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