# Tokenziation Tokenization is a way to break down a string of continuous text into small individual chunks called tokens, each token can be a word/character/sub-word. Different tokenization schemes can be used based on different aspects. So let's say your tokenizer divided the whole text corpus into $$T$$ tokens i.e. there are your text is divided into total $$T$$chunks of smaller words, characters, sub-words, etc. **Now this** $$T$$ **becomes the Vocabulary size of your model.** Each token has an `token_id` $$\in \[1, T]$$. {% embed url="" %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://theshank.gitbook.io/ai/transformers/tokenziation.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.