How To Generate Text Using Markovify and Python

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Introduction to Text Generation with Markovify and Python

Markov chains are a type of statistical model that can be used to generate text. They work by tracking the probability of a given word appearing after a previous word. This allows you to create a model of a language that can be used to generate new text that is similar to the text that was used to train the model.

Markovify is a Python library that makes it easy to generate text using Markov chains. It provides a simple interface that allows you to create a Markov chain model from a corpus of text. You can then use this model to generate new text, either as a single sentence or as a longer piece of text.

In this tutorial, we will learn how to generate text using Markovify and Python. We will start by creating a Markov chain model from a corpus of text. Then, we will use this model to generate new text.

To install Markovify, open a terminal and run the following command:

pip install markovify

Generate text

import markovify

model = markovify.Text(open('data.txt', 'r', errors='ignore').read())

print(model.make_sentence())

In this example, I used text from Lorem ipsum and saved it into data.txt
https://www.lipsum.com/feed/html

result

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