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merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +umt5-base/tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/ACE-Step-v1-3.5B/README.md b/ACE-Step-v1-3.5B/README.md new file mode 100644 index 0000000000000000000000000000000000000000..54282c2816e4f28d6ce93bc705761a599546c9a9 --- /dev/null +++ b/ACE-Step-v1-3.5B/README.md @@ -0,0 +1,122 @@ +--- +license: apache-2.0 +tags: +- music +- text2music +- acestep +pipeline_tag: text-to-audio +language: +- en +- zh +- de +- fr +- es +- it +- pt +- pl +- tr +- ru +- cs +- nl +- ar +- ja +- hu +- ko +- hi +--- + +# ACE-Step: A Step Towards Music Generation Foundation Model + +![ACE-Step Framework](https://github.com/ACE-Step/ACE-Step/raw/main/assets/ACE-Step_framework.png) + +## Model Description + +ACE-Step is a novel open-source foundation model for music generation that overcomes key limitations of existing approaches through a holistic architectural design. It integrates diffusion-based generation with Sana's Deep Compression AutoEncoder (DCAE) and a lightweight linear transformer, achieving state-of-the-art performance in generation speed, musical coherence, and controllability. + +**Key Features:** +- 15× faster than LLM-based baselines (20s for 4-minute music on A100) +- Superior musical coherence across melody, harmony, and rhythm +- full-song generation, duration control and accepts natural language descriptions + +## Uses + +### Direct Use +ACE-Step can be used for: +- Generating original music from text descriptions +- Music remixing and style transfer +- edit song lyrics + +### Downstream Use +The model serves as a foundation for: +- Voice cloning applications +- Specialized music generation (rap, jazz, etc.) +- Music production tools +- Creative AI assistants + +### Out-of-Scope Use +The model should not be used for: +- Generating copyrighted content without permission +- Creating harmful or offensive content +- Misrepresenting AI-generated music as human-created + +## How to Get Started + +see: https://github.com/ace-step/ACE-Step + +## Hardware Performance + +| Device | 27 Steps | 60 Steps | +|---------------|----------|----------| +| NVIDIA A100 | 27.27x | 12.27x | +| RTX 4090 | 34.48x | 15.63x | +| RTX 3090 | 12.76x | 6.48x | +| M2 Max | 2.27x | 1.03x | + +*RTF (Real-Time Factor) shown - higher values indicate faster generation* + + +## Limitations + +- Performance varies by language (top 10 languages perform best) +- Longer generations (>5 minutes) may lose structural coherence +- Rare instruments may not render perfectly +- Output Inconsistency: Highly sensitive to random seeds and input duration, leading to varied "gacha-style" results. +- Style-specific Weaknesses: Underperforms on certain genres (e.g. Chinese rap/zh_rap) Limited style adherence and musicality ceiling +- Continuity Artifacts: Unnatural transitions in repainting/extend operations +- Vocal Quality: Coarse vocal synthesis lacking nuance +- Control Granularity: Needs finer-grained musical parameter control + +## Ethical Considerations + +Users should: +- Verify originality of generated works +- Disclose AI involvement +- Respect cultural elements and copyrights +- Avoid harmful content generation + + +## Model Details + +**Developed by:** ACE Studio and StepFun +**Model type:** Diffusion-based music generation with transformer conditioning +**License:** Apache 2.0 +**Resources:** +- [Project Page](https://ace-step.github.io/) +- [Demo Space](https://huggingface.co/spaces/ACE-Step/ACE-Step) +- [GitHub Repository](https://github.com/ACE-Step/ACE-Step) + + +## Citation + +```bibtex +@misc{gong2025acestep, + title={ACE-Step: A Step Towards Music Generation Foundation Model}, + author={Junmin Gong, Wenxiao Zhao, Sen Wang, Shengyuan Xu, Jing Guo}, + howpublished={\url{https://github.com/ace-step/ACE-Step}}, + year={2025}, + note={GitHub repository} +} +``` + +## Acknowledgements +This project is co-led by ACE Studio and 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+ +

+ +

+ Demo 🎶  |  📑 Paper +
+ YuE-s1-7B-anneal-en-cot 🤗  |  YuE-s1-7B-anneal-en-icl 🤗  |  YuE-s1-7B-anneal-jp-kr-cot 🤗 +
+ YuE-s1-7B-anneal-jp-kr-icl 🤗  |  YuE-s1-7B-anneal-zh-cot 🤗  |  YuE-s1-7B-anneal-zh-icl 🤗 +
+ YuE-s2-1B-general 🤗  |  YuE-upsampler 🤗 +

+ + +--- +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**](https://map-yue.github.io/) for amazing vocal performance. + +Pop:Quiet Evening + +Metal: Step Back + + + +## News and Updates +* 📌 Join Us on Discord! [join discord](https://discord.gg/ssAyWMnMzu) + +* **2025.03.12 🔥 Paper Released🎉**: We now release [YuE technical report](https://arxiv.org/abs/2503.08638)!!! 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). +* **2025.02.07 🎉** Get YuE for Windows on [pinokio](https://pinokio.computer). + +* **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](https://x.com/abrakjamson/status/1885932885406093538), music style transfer [demo by @cocktailpeanut](https://x.com/cocktailpeanut/status/1886456240156348674), 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](https://www.youtube.com/watch?v=RSMNH9GitbA). +* **2025.01.26 🔥**: We have released the **YuE** series. + + +## Quickstart + +Please check our [github](https://github.com/multimodal-art-projection/YuE.git) for easy quickstart. + +--- + +## License Agreement \& Disclaimer +- 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](https://huggingface.co/HKUSTAudio). + +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: :) + +```BibTeX +@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} +} +``` +
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