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nvidia/fastpitch-hifigan-tts
RUN ANYWHEREExpressive and engaging English voices for Q&A assistants, brand ambassadors, and service robots
By running the below commands, you accept the NVIDIA AI Enterprise Terms of Use and the NVIDIA Community Models License.
Pull and run nvidia/fastpitch-hifigan-tts
using Docker (this will download the full model and run it in your local environment)
$ docker login nvcr.io Username: $oauthtoken Password: <PASTE_API_KEY_HERE>
Refer Supported Models for full list of models.
export NGC_API_KEY=<PASTE_API_KEY_HERE> export CONTAINER_NAME=fastpitch-hifigan-tts docker run -it --rm --name=$CONTAINER_NAME \ --runtime=nvidia \ --gpus '"device=0"' \ --shm-size=8GB \ -e NGC_API_KEY=$NGC_API_KEY \ -e NIM_HTTP_API_PORT=9000 \ -e NIM_GRPC_API_PORT=50051 \ -p 9000:9000 \ -p 50051:50051 \ -e NIM_TAGS_SELECTOR=name=fastpitch-hifigan-en-us \ nvcr.io/nim/nvidia/riva-tts:1.3.0
It may take a up to 30 minutes depending on your network speed, for the container to be ready and start accepting requests from the time the docker container is started.
Open a new terminal and run following command to check if the service is ready to handle inference requests
curl -X 'GET' 'http://localhost:9000/v1/health/ready'
If the service is ready, you get a response similar to the following.
{"ready":true}
Install the Riva Python client package
sudo apt-get install python3-pip pip install nvidia-riva-client
Download Riva sample clients
git clone https://github.com/nvidia-riva/python-clients.git
Run Text to Speech inference
python3 python-clients/scripts/tts/talk.py --server 0.0.0.0:50051 --text "Hello, this is a speech synthesizer." --language-code en-US --output output.wav
On running the above command, the synthesized audio file named output.wav will be created.
For more details on getting started with this NIM, visit the NVIDIA NIM Docs.