BPE tokenization does: iteratively merges the most frequent adjacent byte pairs

BPE tokenization does: iteratively merges the most frequent byte pairs

BPE tokenizes text by merging frequent byte pairs

WordPiece tokenization does: similar to BPE but uses likelihood instead of frequency

WordPiece tokenization splits words into subwords based on token likelihood rather than frequency

consistent hashing solves: minimizes key redistribution when servers are added/removed

Consistent hashing minimizes key redistribution when servers are added/removed

subword tokenization solves: handles rare words by breaking into known pieces

Subword tokenization solves rare word handling by breaking into known pieces

SentencePiece does differently from BPE: operates on raw text including whitespace

SentencePiece tokenizes text without pre-tokenization, preserving whitespace

Overlapping subproblems

Ever calculated a huge Fibonacci sequence by hand?