TokEval: A Tokenizer Evaluation Suite
Language model tokenizers are typically selected with minimal evaluation, despite the fact that their design choices directly impact model capabilities. This can be partly attributed to a limited understanding of which tokenizer properties affect which aspects of downstream performance. We introduce TokEval, a framework of tokenizer evaluation metrics that goes beyond standard measures like fertility and compression rate to capture linguistically and structurally meaningful properties, e.g., UTF-8 character boundary integrity and digit place-value boundary alignment for mathematics. To validat
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- PossiblePossibly related (embedding) · 54%GigaToken: ~1000x faster Language model tokenization →
- LinkedLinked via arxiv author · 85%Clara Meister →
“TokEval: A Tokenizer Evaluation Suite”
