Introduction to How LLMS works
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How LLMs Work – Tokenization Explained
- Summary • 7 pages • 2025
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This document explains how large language models (LLMs) process text through tokenization rather than reading words directly. It visually covers key concepts such as subword tokenization, Byte Pair Encoding (BPE), token vocabularies, and why different languages and symbols consume different numbers of tokens.
The material is well suited as an introductory overview for students or learners interested in understanding how AI models handle language and how tokenization impacts prompting and costs.
Summary
How LLMs Work – Tokenization Explained
Last document update:
ago
This document explains how large language models (LLMs) process text through tokenization rather than reading words directly. It visually covers key concepts such as subword tokenization, Byte Pair Encoding (BPE), token vocabularies, and why different languages and symbols consume different numbers of tokens. The material is well suited as an introductory overview for students or learners interested in understanding how AI models handle language and how tokenization impacts prompting and costs.
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