This is an example of text generation using NGrams. To start the text generation, you pick a text:
- "fairy tales": A collection of Grim brother fairy tales
- "green eggs and ham": The Dr. Seuss classic
- "gucci gang": The popular and repetitive song
- "jared": My common application essay
- "romance": A 19th century erotic novel
- "sherlock holmes": All the Sherlock Holmes books
- "speeches": A transcript of a trump speech
- "trump": Trump's tweets up to some point in 2018
After that you need to pick the order of gram you want to use. 10 will create text very similar if not exactly the same as the source text. 1 will create sort of logical statements sometimes. Then you pick a starting word (it must be a word in the text) and the program wil generate text until it starts to loop.