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:
- 6f73b0253a5582b159f0d159b3ad03df8ba649ca4758efc7aa65de9006e86e92
- Size of remote file:
- 1.53 GB
- SHA256:
- 150315748d7c3307cdae2819ee651b32d58385668ca0c4db3d3dcd6e63b77e86
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