👉 Token math refers to the process of calculating and adjusting the number of tokens in a text or dataset, typically used in natural language processing (NLP) tasks. A token is the smallest unit of text that carries meaning, such as a word, part of a word, or punctuation mark. In token math, you might adjust the token count by removing stop words (common words like "the," "is") or by expanding tokens (like converting contractions to their full forms). This process helps in standardizing text data for analysis, improving model performance, and ensuring consistency across different datasets. For example, converting "don't" to "do not" increases the token count by one, while removing "the" from "the quick brown fox" reduces it to a single token.
