README.md

---
license: other
library_name: pytorch
pipeline_tag: text-to-speech
tags:
  - text-to-speech
  - speech-synthesis
  - voice
  - audio
  - sesame
  - mimi
  - llama
---

<div align="center">

<img src="repo_banner.png" alt="Miso TTS 8B" width="100%">
<p>
  <a href="https://misolabs.ai"><img alt="Website" src="https://img.shields.io/badge/Website-misolabs.ai-black?style=for-the-badge"></a>
  <a href="https://huggingface.co/MisoLabs/MisoTTS"><img alt="Hugging Face" src="https://img.shields.io/badge/Hugging%20Face-MisoTTS-yellow?style=for-the-badge"></a>
  <a href="https://github.com/MisoLabsAI"><img alt="GitHub" src="https://img.shields.io/badge/GitHub-MisoLabsAI-181717?style=for-the-badge&logo=github&labelColor=555555"></a>
  <a href="https://x.com/MisoLabsAI"><img alt="X" src="https://img.shields.io/badge/-MisoLabsAI-181717?style=for-the-badge&logo=x&labelColor=555555"></a>
</p>

<p>
  <a href="#quickstart">Quickstart</a> |
  <a href="#model-introduction">Model Introduction</a> |
  <a href="#model-summary">Model Summary</a> |
  <a href="#architecture">Architecture</a> |
  <a href="#links">Links</a>
</p>

</div>

---
# Miso TTS 8B
## Model Introduction

Miso TTS 8B is a text-to-speech model based on the Sesame CSM architecture. It
generates Mimi audio codes from text and optional audio context, using a large
Llama 3.2-style backbone and a smaller autoregressive audio decoder.

The model is designed for high-quality conversational speech generation and
voice continuation from prompt audio. This repository contains the inference
code, model definition, and setup instructions for running Miso TTS locally.

---

## Quickstart

To run the model, use the inference code at our [public repository](https://github.com/MisoLabsAI/MisoTTS), 
or try our demo at misolabs.ai.

## Model Summary

| Item                | Value            |
| ------------------- | ---------------- |
| Model               | Miso TTS 8B      |
| Organization        | Miso Labs        |
| Task                | Text-to-speech   |
| Architecture        | Sesame-style CSM |
| Backbone            | `llama-8B`       |
| Audio decoder       | `llama-300M`     |
| Text vocabulary     | `128,256`        |
| Audio vocabulary    | `2,051`          |
| Audio codebooks     | `32`             |
| Audio tokenizer     | Mimi             |
| Max sequence length | `2,048`          |

### Architecture

Miso TTS 8B uses two transformer components:

- A large backbone transformer that consumes text/audio-frame embeddings.
- A smaller decoder transformer that autoregressively predicts higher-order
  audio codebooks within each frame.

Codebook 0 is
predicted from the backbone hidden state, while codebooks 1 through 31 are
predicted by the audio decoder autoregressively in codebook depth.

---

## Links

- Website: [misolabs.ai](https://misolabs.ai)
- Hugging Face: [MisoLabs/MisoTTS](https://huggingface.co/MisoLabs/MisoTTS)
- GitHub: [MisoLabsAI](https://github.com/MisoLabsAI)
- X: [@MisoLabsAI](https://x.com/MisoLabsAI)