Instructions to use CNcreator0331/DomainShuttle_weight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CNcreator0331/DomainShuttle_weight with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CNcreator0331/DomainShuttle_weight", 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
metadata
license: apache-2.0
pipeline_tag: text-to-video
DomainShuttle: Freeform Open Domain Subject-driven Text-to-video Generation
This repository contains the weights for DomainShuttle, an open-domain subject-driven text-to-video (S2V) generation method presented in DomainShuttle: Freeform Open Domain Subject-driven Text-to-video Generation.
DomainShuttle achieves both high subject fidelity and generative flexibility across diverse open-domain video personalization scenarios by decoupling reference and video features.
- Project Page: DomainShuttle Project Page
- Code: GitHub Repository
Citation
If you find our work useful in your research, please consider citing:
@article{chen2026domainshuttle,
title={DomainShuttle: Freeform Open Domain Subject-driven Text-to-video Generation},
author={Chen, Nan and Cai, Yiyang Caps and Xie, Rongchang and Pan, Junwen and Chen, Cheng and Jia, Weinan and Chen, Zhuowei and Zhou, Wen and Sun, Zhenbang and Luo, Wenhan},
journal={arXiv preprint arXiv:2606.26058},
year={2026}
}