YuE is a series of open-source foundational models designed for music generation, particularly for converting lyrics into complete songs (lyrics2song).
YuE can generate complete songs, including vocal and accompaniment tracks, supporting multiple genres, languages, and vocal techniques.
Model Features
Multilingual Support
Supports lyrics generation and song creation in English, Japanese, Korean, and Chinese.
Multi-Genre Generation
Capable of simulating various music genres, including pop, metal, and more.
Full Song Generation
Generates complete songs with vocals and accompaniment, lasting several minutes.
Incremental Generation
Supports song continuation and incremental generation, offering flexible creative approaches.
Style Transfer
Generates new songs with similar styles by referencing song prompts.
Model Capabilities
Lyrics-to-Song Generation
Multilingual Music Generation
Multi-Genre Music Creation
Song Continuation
Music Style Transfer
Use Cases
Music Creation
Pop Song Generation
Generates complete pop-style songs, such as the example 'Quiet Night'.
Complete songs with vocals and accompaniment
Metal Song Generation
Generates complete metal-style songs, such as the example 'Step Back'.
Complete songs with vocals and accompaniment
Music Style Transfer
Style-Similar Song Generation
Generates new songs with similar styles by referencing song prompts.
Complete songs with similar styles
🚀 YuE (乐)
YuE (乐) is a groundbreaking series of open - source foundation models for music generation. It can transform lyrics into full songs, generating catchy vocal and accompaniment tracks. The model can handle diverse genres, languages, and vocal techniques.
Our model's name is YuE (乐). In Chinese, the word means "music" and "happiness." Some of you may find words that start with Yu hard to pronounce. If so, you can just call it "yeah." We wrote a song with our model's name.
YuE is a groundbreaking series of open - source foundation models designed for music generation, specifically for transforming lyrics into full songs (lyrics2song). It can generate a complete song, lasting several minutes, that includes both a catchy vocal track and accompaniment track. YuE is capable of modeling diverse genres/languages/vocal techniques. Please visit the Demo Page for amazing vocal performance.
Pop: Quiet Evening
Metal: Step Back
✨ Features
Lyrics to Song: Transform lyrics into full - fledged songs, including vocal and accompaniment tracks.
Diverse Modeling: Capable of handling various music genres, languages, and vocal techniques.
Incremental Generation: Support for incremental song generation.
Dual - Track ICL Mode: Generate new songs in a similar style based on a reference song.
📚 News and Updates
📌 Join Us on Discord!
2025.03.12 🔥 Paper Released🎉: We now release YuE technical report!!! We discuss all the technical details, findings, and lessons learned. Enjoy, and feel free to cite us~
2025.03.11 🫶 Now YuE supports incremental song generation!!! See [YuE - UI by joeljuvel](https://github.com/joeljuvel/YuE - UI). YuE - UI is a Gradio - based interface supporting batch generation, output selection, and continuation. You can flexibly experiment with audio prompts and different model settings, visualize your progress on an interactive timeline, rewind actions, quickly preview audio outputs at stage 1 before committing to refinement, and fully save/load your sessions (JSON format). Optimized to run smoothly even on GPUs with just 8GB VRAM using quantized models.
2025.02.17 🫶 Now YuE supports music continuation and Google Colab! See [YuE - extend by Mozer](https://github.com/Mozer/YuE - extend).
2025.01.30 🔥 Inference Update: We now support dual - track ICL mode! You can prompt the model with a reference song, and it will generate a new song in a similar style (voice cloning demo by @abrakjamson, music style transfer demo by @cocktailpeanut, etc.). Try it out! 🔥🔥🔥 P.S. Be sure to check out the demos first—they're truly impressive.
2025.01.30 🔥 Announcement: A New Era Under Apache 2.0 🔥: We are thrilled to announce that, in response to overwhelming requests from our community, YuE is now officially licensed under the Apache 2.0 license. We sincerely hope this marks a watershed moment—akin to what Stable Diffusion and LLaMA have achieved in their respective fields—for music generation and creative AI. 🎉🎉🎉
2025.01.29 🎉: We have updated the license description. we ENCOURAGE artists and content creators to sample and incorporate outputs generated by our model into their own works, and even monetize them. The only requirement is to credit our name: YuE by HKUST/M - A - P (alphabetic order).
2025.01.28 🫶: Thanks to Fahd for creating a tutorial on how to quickly get started with YuE. Here is his demonstration.
2025.01.26 🔥: We have released the YuE series.
🚀 Quick Start
NOTE: This is a checkpoint from one of our early experiments, which trained on 500B tokens of data. It does not support adding structure tags to lyrics, nor timbre tags, only fixed tags for a few genres of music. We don't recommend using it for music creation, as the results may not be too good. We release it for research purposes at the request of the community.
Please check our [github](https://github.com/multimodal - art - projection/YuE.git) for easy quickstart.
📄 License
The YuE model (including its weights) is now released under the Apache License, Version 2.0. We do not make any profit from this model, and we hope it can be used for the betterment of human creativity.
Use & Attribution:
We encourage artists and content creators to freely incorporate outputs generated by YuE into their own works, including commercial projects.
We encourage attribution to the model’s name (“YuE by HKUST/M - A - P”), especially for public and commercial use.
Originality & Plagiarism: It is the sole responsibility of creators to ensure that their works, derived from or inspired by YuE outputs, do not plagiarize or unlawfully reproduce existing material. We strongly urge users to perform their own due diligence to avoid copyright infringement or other legal violations.
Recommended Labeling: When uploading works to streaming platforms or sharing them publicly, we recommend labeling them with terms such as: “AI - generated”, “YuE - generated", “AI - assisted” or “AI - auxiliated”. This helps maintain transparency about the creative process.
Disclaimer of Liability:
We do not assume any responsibility for the misuse of this model, including (but not limited to) illegal, malicious, or unethical activities.
Users are solely responsible for any content generated using the YuE model and for any consequences arising from its use.
By using this model, you agree that you understand and comply with all applicable laws and regulations regarding your generated content.
🙏 Acknowledgements
The project is co - lead by HKUST and M - A - P (alphabetic order). Also thanks moonshot.ai, bytedance, 01.ai, and geely for supporting the project.
A friendly link to HKUST Audio group's huggingface space.
We deeply appreciate all the support we received along the way. Long live open - source AI!
📑 Citation
If you find our paper and code useful in your research, please consider giving a star :star: and citation :pencil: :)
@misc{yuan2025yuescalingopenfoundation,
title={YuE: Scaling Open Foundation Models for Long-Form Music Generation},
author={Ruibin Yuan and Hanfeng Lin and Shuyue Guo and Ge Zhang and Jiahao Pan and Yongyi Zang and Haohe Liu and Yiming Liang and Wenye Ma and Xingjian Du and Xinrun Du and Zhen Ye and Tianyu Zheng and Yinghao Ma and Minghao Liu and Zeyue Tian and Ziya Zhou and Liumeng Xue and Xingwei Qu and Yizhi Li and Shangda Wu and Tianhao Shen and Ziyang Ma and Jun Zhan and Chunhui Wang and Yatian Wang and Xiaowei Chi and Xinyue Zhang and Zhenzhu Yang and Xiangzhou Wang and Shansong Liu and Lingrui Mei and Peng Li and Junjie Wang and Jianwei Yu and Guojian Pang and Xu Li and Zihao Wang and Xiaohuan Zhou and Lijun Yu and Emmanouil Benetos and Yong Chen and Chenghua Lin and Xie Chen and Gus Xia and Zhaoxiang Zhang and Chao Zhang and Wenhu Chen and Xinyu Zhou and Xipeng Qiu and Roger Dannenberg and Jiaheng Liu and Jian Yang and Wenhao Huang and Wei Xue and Xu Tan and Yike Guo},
year={2025},
eprint={2503.08638},
archivePrefix={arXiv},
primaryClass={eess.AS},
url={https://arxiv.org/abs/2503.08638},
}
@misc{yuan2025yue,
title={YuE: Open Music Foundation Models for Full-Song Generation},
author={Ruibin Yuan and Hanfeng Lin and Shawn Guo and Ge Zhang and Jiahao Pan and Yongyi Zang and Haohe Liu and Xingjian Du and Xeron Du and Zhen Ye and Tianyu Zheng and Yinghao Ma and Minghao Liu and Lijun Yu and Zeyue Tian and Ziya Zhou and Liumeng Xue and Xingwei Qu and Yizhi Li and Tianhao Shen and Ziyang Ma and Shangda Wu and Jun Zhan and Chunhui Wang and Yatian Wang and Xiaohuan Zhou and Xiaowei Chi and Xinyue Zhang and Zhenzhu Yang and Yiming Liang and Xiangzhou Wang and Shansong Liu and Lingrui Mei and Peng Li and Yong Chen and Chenghua Lin and Xie Chen and Gus Xia and Zhaoxiang Zhang and Chao Zhang and Wenhu Chen and Xinyu Zhou and Xipeng Qiu and Roger Dannenberg and Jiaheng Liu and Jian Yang and Stephen Huang and Wei Xue and Xu Tan and Yike Guo},
howpublished={\url{https://github.com/multimodal-art-projection/YuE}},
year={2025},
note={GitHub repository}
}