Video-to-Video
Diffusers
Safetensors
English
JoyVideoEditPipeline
video
video-editing
reference-image-guided
autoregressive-diffusion
Instructions to use jdopensource/JoyAI-Video-Edit-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdopensource/JoyAI-Video-Edit-Diffusers 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-Diffusers", 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:
- fe70f8f51f8e25589517617293fa17270b7cc001c550876bbd1ea4d5b63833bf
- Size of remote file:
- 1.53 GB
- SHA256:
- 32d24ce9000dfee1f81b51200381bcd62afbfb0bae5ef1c38b8ec635d4c5bb87
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