Instructions to use jdopensource/JoyAI-Video-Edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdopensource/JoyAI-Video-Edit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jdopensource/JoyAI-Video-Edit", 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:
- 1c6e2b95cbf925b006ed75b0993596cf6e0aa502d39492eef2ac12ae0acbc19a
- Size of remote file:
- 32.5 GB
- SHA256:
- acc90774bb72c80ffb2b2c93f7ef539da4f993a47c6d44d7423fba2aff8f1aa6
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