ComfyUI-TangoFlux

ComfyUI Custom Nodes for "TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching". These nodes, adapted from the official implementations, generates high-quality 44.1kHz audio up to 30 seconds using just a text promptproduction.

Installation

1. Navigate to your ComfyUI's custom_nodes directory:

cd ComfyUI/custom_nodes

2. Clone this repository:

git clone https://github.com/LucipherDev/ComfyUI-TangoFlux

3. Install requirements:

cd ComfyUI-TangoFlux
python install.py

Or Install via ComfyUI Manager

Check out some demos from the official demo page

Example Workflow

Usage

All the necessary models should be automatically downloaded when the TangoFluxLoader node is used for the first time.

Models can also be downloaded using the install.py script

Manual Download:

• Download TangoFlux from here and put everything in models/tangoflux (make sure to include the config files)
• Download text encoders from here and put everything in models/text_encoders/google-flan-t5-large (make sure to include the config files)

The nodes can be found in "TangoFlux" category as TangoFluxLoader, TangoFluxSampler, TangoFluxVAEDecodeAndPlay.

TeaCache can speedup TangoFlux 2x without much audio quality degradation, in a training-free manner.

📈 Inference Latency Comparisons on a Single A800

TangoFlux	TeaCache (0.25)	TeaCache (0.4)
~4.08 s	~2.42 s	~1.95 s

Citation

@misc{hung2024tangofluxsuperfastfaithful,
      title={TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching and Clap-Ranked Preference Optimization}, 
      author={Chia-Yu Hung and Navonil Majumder and Zhifeng Kong and Ambuj Mehrish and Rafael Valle and Bryan Catanzaro and Soujanya Poria},
      year={2024},
      eprint={2412.21037},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2412.21037}, 
}

@article{liu2024timestep,
  title={Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model},
  author={Liu, Feng and Zhang, Shiwei and Wang, Xiaofeng and Wei, Yujie and Qiu, Haonan and Zhao, Yuzhong and Zhang, Yingya and Ye, Qixiang and Wan, Fang},
  journal={arXiv preprint arXiv:2411.19108},
  year={2024}
}