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Question Answering Notebook

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End to End workflow for question answering starting with training in TAO Toolkit and deployment using Riva.
Latest Version
April 4, 2023
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Question Answering

The Question Answering task in NLP pertains to building a model which can answer questions posed in natural language. Many datasets (including SQuAD, the dataset we use in this notebook) pose this as a reading comprehension task i.e. given a question and a context, the goal is to predict the span within the context with a start and end position which indicates the answer to the question. For every word in the training dataset we predict:

  • likelihood this word is the start of the span
  • likelihood this word is the end of the span

The best place to get started with TAO Toolkit - Question Answering would be the TAO - Question Answering jupyter notebooks. This resource has two notebooks included.

  1. Training: Sample workflow for training a question answering model and export the model to a .riva file
  2. Deployment: Sample workflow to consume the .riva file and deploy it to Riva.

If you are a seasoned Conversation AI developer we recommend installing TAO and referring to the TAO documentation for usage information.


Please make sure to install the following before proceeding further:

  • python 3.6.9
  • docker-ce > 19.03.5
  • docker-API 1.40
  • nvidia-container-toolkit > 1.3.0-1
  • nvidia-container-runtime > 3.4.0-1
  • nvidia-docker2 > 2.5.0-1
  • nvidia-driver >= 455.23

Note: A compatible NVIDIA GPU would be required.


We recommend that you install TAO Toolkit inside a virtual environment. The steps to do the same are as follows.

virtualenv -p python3 
source /bin/activate
pip install jupyter notebook # If you need to run the notebooks

TAO Toolkit is a python package that is hosted in nvidia python package index. You may install by using python’s package manager, pip.

pip install nvidia-pyindex
pip install nvidia-tao

To download the jupyter notebook please:

  1. Download the samples using the ngc cli with the following command
ngc registry resource download-version "nvidia/tao/questionanswering_notebook:v1.0"
  1. Instantiate the jupyter notebook server
jupyter notebook --ip --allow-root --port 8888


By downloading and using the models and resources packaged with TAO Toolkit Conversational AI, you would be accepting the terms of the Riva license