Instructions to use LanguageBind/Open-Sora-Plan-v1.3.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LanguageBind/Open-Sora-Plan-v1.3.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LanguageBind/Open-Sora-Plan-v1.3.0", 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
Add pipeline tag
Browse filesThis PR ensures the model can be found at:
* https://huggingface.co/papers/2412.00131
* https://huggingface.co/models?pipeline_tag=text-to-video&sort=trending
README.md
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license: mit
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## BibTeX
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```bibtex
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```
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## Latest DOI
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license: mit
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pipeline_tag: text-to-video
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## BibTeX
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```bibtex
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@misc{lin2024opensoraplanopensourcelarge,
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title={Open-Sora Plan: Open-Source Large Video Generation Model},
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author={Bin Lin and Yunyang Ge and Xinhua Cheng and Zongjian Li and Bin Zhu and Shaodong Wang and Xianyi He and Yang Ye and Shenghai Yuan and Liuhan Chen and Tanghui Jia and Junwu Zhang and Zhenyu Tang and Yatian Pang and Bin She and Cen Yan and Zhiheng Hu and Xiaoyi Dong and Lin Chen and Zhang Pan and Xing Zhou and Shaoling Dong and Yonghong Tian and Li Yuan},
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year={2024},
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eprint={2412.00131},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2412.00131},
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}
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```
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## Latest DOI
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