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#
docker pull ghcr.io/coqui-ai/tts-cpu
GPU version#
docker pull ghcr.io/coqui-ai/tts
Building your own image#
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#
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
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#
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#
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!