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Token

As explained in LLMs in Production

A token is a discrete unit of text representation processed by a language model.

Tokenization turns raw text into numerical input by splitting it into units that may be as small as a character or as large as a word. The resulting tokenized text is fed into the language model during training. section 5.2.1

How LLMs in Production covers it

How deep it goes
Places tokenization in preprocessing and follows the resulting units into model training.
Examples
Gives possible unit sizes from single characters to words, without a worked tokenization example.
What you can do after
Understand how tokenization converts raw text into numerical input for language-model training.
How it connects
Links tokens with preprocessing, numerical representations, and language-model training.

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This explainer was generated by Manning's knowledge graph from the text of LLMs in Production. The section links point to the parts of the book it draws on.