bytepairbased
Bytepairbased is a term used to describe approaches that rely on byte-pair encoding as the core mechanism for tokenizing data. The method starts from an initial symbol set (often bytes or characters) and iteratively replaces the most frequent adjacent symbol pair with a new symbol. This process continues until a target vocabulary size or another stopping criterion is reached, producing a vocabulary of subword units that capture common sequences.
In natural language processing, byte-pair based tokenization helps manage out-of-vocabulary words and morphologically rich languages by
Applications and considerations: Bytepairbased tokenizers are widely used in training large language models because they offer
See also: Byte Pair Encoding; subword tokenization; SentencePiece; neural machine translation.