LibreAI / Audio / MOSS-TTS-Nano
// audio · OpenMOSS/MOSS-TTS-Nano

MOSS-TTS-Nano

MOSS-TTS-Nano es un proyecto de audio de código abierto de OpenMOSS (OpenMOSS/MOSS-TTS-Nano en GitHub). Tiene 4.457 estrellas en GitHub y 557 bifurcaciones, se publica bajo la licencia Apache-2.0 y se actualizó por última vez en GitHub el 6 de septiembre de 2026.

MOSS-TTS-Nano: a 0.1B open multilingual speech model that clones voices and streams in real time on CPU

★ 4,5k estrellas⑂ 557 bifurcacionesApache-2.0actualizado sep 2026
▦ visual: el README de este proyecto no incluye ninguna captura incrustable,
así que aquí va un marcador. La guía de abajo está completa de todos modos.
// datos del proyecto

Datos del proyecto

Estrellas en GitHub
4.457
Bifurcaciones
557
Licencia
Apache-2.0
Última actualización en GitHub
6 de septiembre de 2026
Categoría
Audio
Tipo de ficha
Guía de instalación completa
Sitio oficial
Official site
// cómo funciona

Cómo funciona

  1. Set up the environment

    Create the documented Python 3.12 Conda environment.

  2. Clone and install

    Clone the repo, install requirements, and install the package in editable mode.

  3. Clone a voice

    Run inference with a reference audio clip and the text you want spoken; weights download automatically from Hugging Face.

  4. Serve or fine-tune

    Launch the web demo or CLI server for interactive use, or fine-tune on your own data with the included code.

// características

Por qué gusta tanto

Tiny 0.1B footprint

A very small autoregressive speech model designed to run in real time even on CPU.

20 languages, 48 kHz stereo

Multilingual synthesis with native stereo output at 48 kHz.

Zero-shot voice cloning

Clone a voice from a short reference recording passed as the prompt audio.

Real-time streaming

Streaming inference, including an ONNX runtime the project benchmarks at real-time on one CPU core.

CLI, web demo, and Python API

Generate or serve from the `moss-tts-nano` CLI, a local web UI on port 18083, or Python scripts.

Fine-tuning included

Training code is provided so you can adapt the model to your own voices or data.

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// ejecútalo

Ejecútalo tú mismo

  1. Clone the repository

    Clone the project and enter its directory.

    git clone https://github.com/OpenMOSS/MOSS-TTS-Nano.git
    cd MOSS-TTS-Nano
  2. Create the environment and install

    Create the Conda env, install requirements, and install the package.

    conda create -n moss-tts-nano python=3.12 -y
    conda activate moss-tts-nano
    pip install -r requirements.txt
    pip install -e .
  3. Clone a voice and generate

    Run inference with a reference clip (weights auto-download), or start the web demo with `python app.py`.

    python infer.py --prompt-audio-path assets/audio/zh_1.wav --text "Hello from MOSS-TTS-Nano."
// casos de uso

Qué puedes crear

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// preguntas frecuentes

Preguntas frecuentes

Who maintains MOSS-TTS-Nano?

OpenMOSS, the MOSI.AI research lab, which also publishes the larger MOSS-TTS model family.

Is it free?

Yes — code and weights are Apache-2.0 licensed and downloadable from Hugging Face.

Does it need a paid API key?

No. It runs entirely locally; a GPU is optional since it is designed for CPU real-time use.

How does it compare to the full MOSS-TTS?

Nano is the 0.1B edge-friendly member of the family: far smaller and CPU-capable, trading some of the flagship 8B model's fidelity for speed and deployability.

How do I get started?

Create the Python 3.12 Conda env, clone, `pip install -r requirements.txt && pip install -e .`, then run `python infer.py` with a prompt audio file — or `python app.py` for the web demo.

// sigue explorando

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// alternativas

Alternativas en Audio

Los demás proyectos de Audio con más estrellas del catálogo de LibreAI: la lista realista de alternativas si MOSS-TTS-Nano no es lo que buscas.

// más en audio

Más en Audio

Proyectos de Audio cercanos en el catálogo, los más próximos en estrellas a MOSS-TTS-Nano: sigue explorando a ambos lados.

Consigue MOSS-TTS-Nano

Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.