Setting Up TangoFlux for Text-to-Audio Generation on Ubuntu

Anas Mohammad -

TangoFlux is an open-source text-to-audio model designed to generate high-quality, realistic audio clips from simple text prompts.

Developed by Declare Lab and powered by Stability AI, it utilizes advanced machine learning techniques like Flow Matching and CLAP-Ranked Preference Optimization (CRPO) to produce audio that aligns closely with user expectations.

This guide will walk you through setting up TangoFlux on Ubuntu, covering installation, usage, troubleshooting, and real-world applications.

Overview of TangoFlux

Key Features

  • High-Quality Audio Generation – Produces audio clips up to 30 seconds long at a 44.1 kHz sample rate.
  • Fast Inference – Generates audio in around 3.7 seconds on an A40 GPU, making it suitable for real-time applications.
  • Open Source – Fully customizable, allowing modifications based on user requirements.
  • User-Friendly Interface – Simple text prompts enable easy audio generation.

Technical Architecture

TangoFlux employs a combination of Diffusion Transformer (DiT) and Multimodal Diffusion Transformer (MMDiT) architectures. It follows a three-stage training process:

  1. Pre-training – Initial training on large datasets for basic audio generation.
  2. Fine-tuning – Optimized for specific datasets to improve performance.
  3. Preference Optimization – Utilizes CRPO to enhance output quality based on user preferences.

Setting Up TangoFlux on Ubuntu

Prerequisites

Ensure your system meets the following requirements before installation:

  • OS: Ubuntu 20.04 or later
  • Python: Version 3.8 or higher
  • RAM: At least 6 GB for smooth operation
  • GPU: NVIDIA GPU (e.g., A40, RTX series) for optimal performance

Step 1: Install Python and Pip

If Python isn’t installed, run:

sudo apt update
sudo apt install python3 python3-pip

Step 2: Install Required Libraries

Install dependencies via pip:

pip install torch torchaudio transformers

Step 3: Clone the TangoFlux Repository

Retrieve the source code from GitHub:

git clone https://github.com/declare-lab/TangoFlux.git
cd TangoFlux

Step 4: Install TangoFlux

Use pip to install TangoFlux in editable mode:

pip install -e .

Step 5: Verify Installation

Ensure the installation was successful:

import tangoflux
print(tangoflux.__version__)

If the version number appears without errors, the setup is complete.

Generating Audio with TangoFlux

Step 1: Import Necessary Libraries

import torchaudio
from tangoflux import TangoFluxInference
from IPython.display import Audio

Step 2: Initialize the Model

model = TangoFluxInference(name='declare-lab/TangoFlux')

Step 3: Generate Audio from a Text Prompt

audio = model.generate('Hammer slowly hitting the wooden table', steps=50, duration=10)

Step 4: Play or Save the Generated Audio

Play audio directly in a notebook:

Audio(data=audio, rate=44100)

Save it as a WAV file:

torchaudio.save('output.wav', audio.unsqueeze(0), sample_rate=44100)

Troubleshooting Common Issues

1. Installation Errors

Verify that dependencies are correctly installed and that your Python version is compatible.

2. Insufficient RAM

Close unnecessary applications or upgrade hardware if memory-related errors occur.

3. Audio Quality Issues

Increase the sampling steps in the generate function for better output quality, but note that this may increase processing time.

Practical Applications of TangoFlux

TangoFlux can be applied across various industries:

  • Game Development – Generates dynamic sound effects for interactive experiences.
  • Film Production – Creates realistic soundscapes for movie scenes.
  • Education – Enhances learning materials with custom-generated audio.
  • Accessibility Tools – Converts written content into audio for visually impaired users.

Conclusion

TangoFlux offers a seamless text-to-audio generation experience on Ubuntu, enabling high-quality, AI-driven sound production.

With its powerful architecture and ease of use, it opens new possibilities in gaming, film production, education, and accessibility. By following this guide, you can harness TangoFlux effectively for your projects.