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Comment on GigaToken: ~1000x faster Language model tokenization

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Is tokenizing really the bottleneck? If we go from 20ms to 15ms does it really matter?

You sound like someone who used to write fastruby

Never heard of fast ruby. My point is tokenizing is rarely a bottleneck, as 99% of time is spent in inference.

So you speed up 1% of the pipeline by some factor, and the end result is unobservable for a human.

Time to first token is observable by a human, and they’re reporting up to 10% reduction there.

Plus, inference is not the only place tokenization happens. This can make a big difference during development of ML models.

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