Text Summarizer

Overview

This model takes a JSON input that encapsulates some text snippets and returns a text summary that represents the key information or message in the input text. The model was trained on the CNN / Daily Mail dataset. The model has a vocabulary of approximately 200k words. The model is based on the ACL 2017 paper, Get To The Point: Summarization with Pointer-Generator Networks.

Model Metadata

References

• A. See, P. J. Liu, C. D. Manning, Get To The Point: Summarization with Pointer-Generator Networks, ACL, 2017.

• The text summarization repository

Licenses

Options available for deploying this model

This model can be deployed using the following mechanisms:

• Deploy from Dockerhub:

  docker run -it -p 5000:5000 codait/max-text-summarizer
  

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• Deploy on Red Hat OpenShift:

  Follow the instructions for the OpenShift web console or the OpenShift Container Platform CLI in this tutorial and specify codait/max-text-summarizer as the image name.

• Deploy on Kubernetes:

  kubectl apply -f https://raw.githubusercontent.com/IBM/MAX-Text-Summarizer/master/max-text-summarizer.yaml
  

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  A more elaborate tutorial on how to deploy this MAX model to production on IBM Cloud can be found here.

• Locally: follow the instructions in the model README on GitHub

Example Usage

You can test or use this model

• using cURL
• in a serverless app

Test the model using cURL

Once deployed, you can test the model from the command line. For example:

$ curl -d @samples/sample1.json -H "Content-Type: application/json" -XPOST http://localhost:5000/model/predict

You should see a JSON response like that below:

{
  "status": "ok",
  "summary_text": [
      ["nick gordon 's father -lrb- left and right -rrb- gave an interview about the 25-year-old fiance of bobbi kristina brown . it has been reported that gordon , 25 , has threatened suicide and has been taking xanax since . whitney houston 's daughter was found unconscious in a bathtub in january . on wednesday , access hollywood spoke exclusively to gordon 's stepfather about his son 's state of mind . "]
  ]
}

Test the model in a serverless app

You can utilize this model in a serverless application by following the instructions in the Leverage deep learning in IBM Cloud Functions tutorial.

Resources and Contributions

If you are interested in contributing to the Model Asset Exchange project or have any queries, please follow the instructions here.