This repository provides instructions for deploying and running Qwen3 Text-to-Speech (TTS) services.
本项目用于部署和运行 Qwen3 文本转语音(TTS) 服务,支持本地 Conda 环境与 Docker 两种部署方式。
- Requirements | 环境要求
- Initial Setup | 初次创建环境
- Dependency Installation | 安装依赖
- SoX Installation (Windows) | 安装 SoX(Windows)
- Model Download | 模型下载
- Run & Stop | 启动与停止
- Docker Deployment | Docker 构建方式
- OS:Windows(Docker 部署可跨平台)
- Python:3.12
- CUDA:12.4(GPU 推理需要)
- Conda(Anaconda / Miniconda)
- NVIDIA Driver correctly installed
conda create -n qwen-tts python=3.12 -yconda activate qwen-ttspip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124pip install -U qwen-ttspip install fastapi uvicorn jinja2 python-multipart soundfileSoX is required for audio processing during TTS inference.
SoX 是 TTS 推理所需的音频处理工具。
Official website 官方地址:
https://sourceforge.net/projects/sox/files/sox/
Download win32.exe installer.
下载 win32.exe 安装包。
Recommended installation path:
建议安装路径:
C:\sox
- Right-click This PC → Properties
- Advanced system settings → Environment Variables
- Add the following path to
Path(System Variables)
C:\sox
Restart terminal and run:
sox --versionIf the version is displayed, installation is successful.
若显示版本号,则表示安装成功。
pip install modelscopemodelscope download --model Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice --local_dir ./Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
modelscope download --model Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign --local_dir ./Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign
modelscope download --model Qwen/Qwen3-TTS-12Hz-1.7B-Base --local_dir ./Qwen/Qwen3-TTS-12Hz-1.7B-Baseconda activate qwen-tts
python main.pyconda deactivateIf you prefer containerized deployment, use Docker Compose.
如果你希望使用容器化部署,可使用 Docker Compose。
docker-compose up -d --build- This guide assumes basic knowledge of Conda and Docker.
本文档默认你具备 Conda 与 Docker 的基础使用经验。 - For GPU Docker usage, ensure
nvidia-container-toolkitis installed.
使用 GPU Docker 请确保已安装nvidia-container-toolkit。 - Model files are large; initial download may take time.
模型体积较大,首次下载耗时较长,请耐心等待。