vllm-omni/docs/user_guide/examples/offline_inference/fish_speech.md

Fish Speech S2 Pro

Source https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/fish_speech.

This directory contains an offline demo for running Fish Speech S2 Pro (fishaudio/s2-pro) with vLLM Omni. It supports text-only synthesis and voice cloning with reference audio.

Model Overview

Fish Speech S2 Pro is a 4B dual-AR text-to-speech model by FishAudio. It uses:

• Slow AR: Generates semantic tokens autoregressively (Qwen3-based backbone)
• Fast AR: Predicts residual codebook tokens from semantic tokens
• DAC Decoder: Converts codec codes to 44.1 kHz audio waveform

The model produces high-quality speech with voice cloning capabilities.

Prerequisites

Install the fish-speech package for the DAC codec:

pip install fish-speech

Setup

Please refer to the stage configuration documentation to configure memory allocation appropriately for your hardware setup.

Quick Start

Text-Only Synthesis

python end2end.py --text "Hello, this is a test of the Fish Speech text to speech system."

Generated audio files are saved to output_audio/ by default.

Voice Cloning

Provide a reference audio file and its transcript to clone a voice:

python end2end.py \
    --text "Hello, this is a cloned voice." \
    --ref-audio /path/to/reference.wav \
    --ref-text "Transcript of the reference audio."

Streaming Mode

Add --streaming to stream audio chunks progressively via AsyncOmni (requires async_chunk: true in the stage config):

python end2end.py --text "Hello, this is a test." --streaming

Each DAC decoder chunk is logged as it arrives. The final WAV file is written once generation completes.

Configuration

Argument	Default	Description
--text	"Hello, this is a test..."	Text to synthesize
--ref-audio	None	Path to reference audio for voice cloning
--ref-text	None	Transcript of the reference audio
--model	fishaudio/s2-pro	HuggingFace model path
--stage-configs-path	fish_speech_s2_pro.yaml	Path to stage configs YAML
--output-dir	output_audio	Output directory for WAV files
--streaming	False	Enable streaming via AsyncOmni
--stage-init-timeout	600	Stage initialization timeout (seconds)

Notes

• Output audio is 44.1 kHz mono WAV.
• The DAC codec weights (codec.pth) are loaded lazily from the model directory.
• Voice cloning encodes the reference audio using the DAC codec to extract semantic codes, then prepends them as a system message.

Example materials

??? abstract "end2end.py" py --8<-- "examples/offline_inference/fish_speech/end2end.py"