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
File size: 429 Bytes
a88664b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"_class_name": "JoyVideoEditPipeline",
"_diffusers_version": "0.40.0.dev0",
"processor": [
null,
null
],
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"text_encoder": [
null,
null
],
"tokenizer": [
null,
null
],
"transformer": [
"diffusers",
"JoyVideoEditTransformer3DModel"
],
"vae": [
"diffusers",
"AutoencoderKLJoyVideoEdit"
]
}
|