Tokens are essential units in large language models (LLMs) that affect performance and cost. This guide explains tokens, their role in LLMs, and the importance of tokenization. Different methods including word-based, character-based, and subword tokenization are discussed along with strategies to optimize token usage.
Table of contents
Understanding Large Language Model TokensHow Do LLMs Use Tokens?Tokenization: How Text Is Converted into TokensToken Limits and Model ConstraintsLLM Tokenization in PracticePopular Tokenization Algorithms and Their DifferencesConclusionSort: