Tokenization Data
Domain: Data & Datasets
🎯 Motivation
Data about how text is split into tokens. Tokenization quality affects model performance.
📋 Concrete Example
Tokenization: unbelievable -> [un, believ, able] (subword). The model learns these subword units. Good tokenization = better understanding.
🔗 Analogy
Breaking a word into syllables - un-be-liev-a-ble. Each syllable is a unit. Tokenization breaks text into model-understandable units.