Image-to-Video
Diffusers
Safetensors
video-generation
audio-video-generation
reference-to-video
long-video
multi-shot
dmd
Instructions to use jdopensource/JoyAI-Echo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdopensource/JoyAI-Echo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jdopensource/JoyAI-Echo", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Based on LTX-2 by Lightricks Ltd.
Modified by JD.com for academic and research purposes only. Not for commercial use. For commercial use, please contact Lightricks Ltd. Original copyright, license, and attribution notices are retained.
Gemma 3 12B and MSST-WebUI are external runtime dependencies and are not redistributed in this model repository. Users must obtain them separately under their respective licenses.