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
Commit History
-
Upload vace_14b_outputs.tar.gz
Verified signatureaveraging framesd384e81 -
Upload V3_total_4096.zip with huggingface_hub
Verified signature91e12c1 -
Upload ViFedit_total_1024_sdedit.zip with huggingface_hub
Verified signature2464ff5 -
Upload tag.zip
Verified signature36e5157
-
Upload 2DresidualV3_total_4096.zip with huggingface_hub
Verified signaturee77677d -
Upload folder using huggingface_hub
Verified signatureb6573ef -
Upload 2DresidualV3_total_4096_sdedit.zip with huggingface_hub
Verified signatured88a471
-
Upload test_i2v_processed.zip with huggingface_hub
Verified signature48229eb -
initial commit
Verified signature33ee9ad