CosyVoice 模型部署教程CosyVoice 是一个开源的超强 TTS(文本转语音)模型,它支持多种生成模式,具有极强的语音自然可控性。
具有以下特点
可应用于多个场景,如
git clone --recursive https://github.com/FunAudioLLM/CosyVoice.git
# If you failed to clone submodule due to network failures, please run following command until success
cd CosyVoice
git submodule update --init --recursive
conda create -n cosyvoice python=3.8
conda activate cosyvoice
# pynini is required by WeTextProcessing, use conda to install it as it can be executed on all platform.
conda install -y -c conda-forge pynini==2.1.5
pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com
# If you encounter sox compatibility issues
# ubuntu
sudo apt-get install sox libsox-dev
# centos
sudo yum install sox sox-devel
下载预训练 CosyVoice-300M CosyVoice-300M-SFT CosyVoice-300M-Instruct 模型和 CosyVoice-ttsfrd 资源。
# git模型下载,请确保已安装git lfs
mkdir -p pretrained_models
git clone https://www.modelscope.cn/iic/CosyVoice-300M.git pretrained_models/CosyVoice-300M
git clone https://www.modelscope.cn/iic/CosyVoice-300M-SFT.git pretrained_models/CosyVoice-300M-SFT
git clone https://www.modelscope.cn/iic/CosyVoice-300M-Instruct.git pretrained_models/CosyVoice-300M-Instruct
git clone https://www.modelscope.cn/iic/CosyVoice-ttsfrd.git pretrained_models/CosyVoice-ttsfrd
或者,可以解压缩 ttsfrd 资源并安装 ttsfrd 包以获得更好的文本规范化性能。
注意,这一步不是必须的,如果你没有安装 ttsfrd,默认使用 WeTextProcessing。
cd pretrained_models/CosyVoice-ttsfrd/
unzip resource.zip -d .
pip install ttsfrd-0.3.6-cp38-cp38-linux_x86_64.whl
# change iic/CosyVoice-300M-SFT for sft inference, or iic/CosyVoice-300M-Instruct for instruct inference
python3 webui.py --port 50000 --model_dir pretrained_models/CosyVoice-300M

进入webui页面如下:

点击此处,立即体验CosyVoice!
