Docker Images

(docker_images)=

We provide docker images to be able to test TTS without having to setup your own environment.

Using premade images

You can use premade images built automatically from the latest TTS version.

CPU version

bash

docker pull ghcr.io/coqui-ai/tts-cpu

GPU version

bash

docker pull ghcr.io/coqui-ai/tts

Building your own image

bash

docker build -t tts .

Basic inference

Basic usage: generating an audio file from a text passed as argument. You can pass any tts argument after the image name.

CPU version

bash

docker run --rm -v ~/tts-output:/root/tts-output ghcr.io/coqui-ai/tts-cpu --text "Hello." --out_path /root/tts-output/hello.wav

GPU version

For the GPU version, you need to have the latest NVIDIA drivers installed. With nvidia-smi you can check the CUDA version supported, it must be >= 11.8

bash

docker run --rm --gpus all -v ~/tts-output:/root/tts-output ghcr.io/coqui-ai/tts --text "Hello." --out_path /root/tts-output/hello.wav --use_cuda true

Start a server

Starting a TTS server: Start the container and get a shell inside it.

CPU version

bash

docker run --rm -it -p 5002:5002 --entrypoint /bin/bash ghcr.io/coqui-ai/tts-cpu
python3 TTS/server/server.py --list_models #To get the list of available models
python3 TTS/server/server.py --model_name tts_models/en/vctk/vits

GPU version

bash

docker run --rm -it -p 5002:5002 --gpus all --entrypoint /bin/bash ghcr.io/coqui-ai/tts
python3 TTS/server/server.py --list_models #To get the list of available models
python3 TTS/server/server.py --model_name tts_models/en/vctk/vits --use_cuda true

Click there and have fun with the server!