Integrating Conversational AI Models into Riva

While the TAO Toolkit is an excellent resource to train and finetune models, Riva provides resources to deploy those models into scalable services running on GPUs.

Along with the TAO conversational AI package, we provide the following sample resources on NGC to capture the end to end workflow of training a model with TAO and deploying them to Riva.

Conversational AI Task

Jupyter Notebooks

Speech to Text Speech to Text Notebook
Speech to Text Citrinet Speech to Text Citrinet Notebook
Question Answering Question Answering Notebook
Text Classification Text Classification Notebook
Token Classification Token Classification Notebook
Punctuation and Capitalization Punctuation Capitalization Notebook
Intent and Slot Classification Intent Slot Classification Notebook
NGram LM Notebook NGram LM Notebook
Text to Speech Text to Speech Notebook

Each sample resource contain 2 sample notebooks,

  1. To train the respective model using TAO Toolkit and generate an exported .riva

  2. To use this exported .riva file and deploy it to Riva.

You may find more information about the same in the Riva Documentation.

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