
nvidia
parakeet-1.1b-rnnt-multilingual-asr
Run AnywhereHigh accuracy and optimized performance for transcription in 25 languages
Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.
Generate API Key
Pull and Run the NIM
$ 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> docker run -it --rm --name=parakeet-1-1b-rnnt-multilingual \ --runtime=nvidia \ --gpus '"device=0"' \ --shm-size=8GB \ -e 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=mode=str \ nvcr.io/nim/nvidia/parakeet-1-1b-rnnt-multilingual:latest
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.
Test the NIM
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 -U nvidia-riva-client
Download Riva sample clients
git clone https://github.com/nvidia-riva/python-clients.git
Run Speech to Text inference in streaming modes. Riva ASR supports Mono, 16-bit audio in WAV, OPUS and FLAC formats.
python3 python-clients/scripts/asr/transcribe_file.py --server 0.0.0.0:50051 --input-file <path_to_speech_file>
For more details on getting started with this NIM, visit the Riva ASR NIM Docs.