Tokenization serves as a fundamental preprocessing step in language modeling, wherein raw text input is segmented into individual tokens or subword units for computational processing. By breaking down input sequences into discrete tokens, tokenization enables language models to effectively encode and represent the underlying linguistic structure and semantics, facilitating more robust and efficient text generation and comprehension.
