In natural language processing, a token is a sequence of characters that represents a single unit of meaning in a text. In the context of ChatGPT, tokens refer to the individual words or sub-words that make up the input text that the model is processing.

When ChatGPT receives an input text, it first breaks it down into individual tokens, which are then converted into numerical representations (vectors) that the model can use to process the text. This process is called tokenization.

For example, if the input text is "I love pizza", ChatGPT would break it down into three tokens: "I", "love", and "pizza". Each of these tokens would then be assigned a numerical representation that corresponds to its meaning within the model's language model.

Tokenization is an important part of natural language processing, as it allows the model to understand and process the meaning of text at a more granular level, making it possible to generate more accurate and coherent responses to user input.

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