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README.md 1.0 KB

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Named-Entity-Recognition Workshop

In this workshop, we would learn how to automatically style ( bold , Italics, etc. ) a word according to context.

We learn styling from html files automatically and apply them to raw text.

This project is used mainly to demonstrate deep-learning implementation of named-entity-recognition (NER) models.

Preparing the environment (locally)

#####Note: in case you are not using Colab

  1. Make sure Python3 is installed.
  2. You can create you virtual environment (recommended) using python3 -m virtualenv ner_ws
  3. To activate your virtual env, run: source ner_ws/bin/activate
  4. Now install all of the requirements: pip3 install -r requirements.txt

Usage

  1. Run style_extract.py to generate training files from html.
  2. Put the .zip file in the data/ folder.
  3. Run style_learn.py to train an NER model.
  4. Run server.py to evaluate your model in the browser.

For more details, contact me at goren.ml .

Tip!

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