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Using deep complicated NLP to turn your text into my text by arbitrarily swapping words for their synonyms /s

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SirajNet

Using deep complicated NLP to turn your text into my text by arbitrarily swapping words for their synonyms. /s

Usage

usage: main.py [-h] [--text TEXT] [--chance CHANCE] [--file FILE]

optional arguments:
  -h, --help       show this help message and exit
  --text TEXT      your original text
  --chance CHANCE  one in N swap chance
  --file FILE      path to text file containing text

Examples

Entering text in the command line

$ python3 main.py --chance 1 --text "Hello world, it's siraj!"
howdy world, it's siraj!

Providing a text file

$ echo -en "hello world it's siraj and this week i'm\ngoing to show you how Gaussian gates and complex Hilbert\nspaces work. stay cool wizards" > file.txt
$ python3 main.py --chance 1 --file file.txt
how-do-you-do world it's siraj and this week Im
go to show you how Gaussian doors and hard David Hilbert
gaps work. check chill wizards

Requirements

  • TextBlob (pip install textblob)
  • PhD in neural quantum blockchain
  • 5 minutes
  • extensive knowledge of residual capsule reservoir networks
  • stargazing this repository

If running the first time

To allow the Gaussian doors to shine through, you may need to download the wordnet corpus that is part of NLTK which is a dependency of TextBlob. If not, it will generate many complicated Hilbert space errors that which mention that Resource wordnet not found. To resolve this, please do the following in your Python REPL before running:

>>> import nltk
>>> nltk.download('wordnet')

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Using deep complicated NLP to turn your text into my text by arbitrarily swapping words for their synonyms /s

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