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Python-based web application to demonstrate the ability of some state-of-the-art machine learning NLP models at the question-answering task.

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dkedar7/MachineComprehension

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Machine Comprehension (under development)

Web application to demonstrate ability of some state-of-the-art machine learning models at the questions answering task. The models chosen for the first deployment of the app are:

  1. BiDAF - ONNX pre-trained model
  2. DistilBERT - HuggingFace implementation
  3. RoBERTa - Deepset implementation (on Hugging face model zoo)
  4. ALBERT - twmkn9 implmentation (on Hugging face model zoo)

Deployment (work in progress)

The demo deployment will likely utilize Google Build to containerize the application, Google Container Registry for storing and managing a container and Google Cloud Run to deploy it as a web endpoint.

Cloud Run Architecture

More about Google Cloud Run

How to install (work in progress)

Dependencies (work in progress)

You need Python 3 to run this application. Other dependencies can be found in the requirements.txt file.

License

Machine Comprehension uses the MIT license.

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Python-based web application to demonstrate the ability of some state-of-the-art machine learning NLP models at the question-answering task.

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