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Tokens and Embeddings: How LLMs Read Text
1 min readLearnJul 17, 2026
Key Takeaway for Students
LLMs split text into tokens (roughly word pieces) and turn each into a vector of numbers called an embedding. Distances between these vectors capture meaning, which is why models can find similar concepts.
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LLMs split text into tokens (roughly word pieces) and turn each into a vector of numbers called an embedding. Distances between these vectors capture meaning, which is why models can find similar concepts.