Gigatoken: Fastest Tokenizer

https://twitter.com/marcelroed/status/2079642154960564352

by convexstrictly • 1 day ago

24 5 1 day ago

twitter.com

convexstrictly2• 1 day ago

GitHub: https://github.com/marcelroed/gigatoken

Alifatisk• 15 hours ago

They even added a section ”AI Use Disclosure”, beautiful!

benj111• 14 hours ago

I kind of assumed the model would process the text 'directly', from what I understand, wouldn't this be biasing the input based on how you tokenise as it's lossy?

I assume this tradeoff is purely for speed/compression. Or am I missing what's going on here?

convexstrictly2• 14 hours ago

Tokenization is done on the CPU. Models never see the raw characters. That's why you get trick questions like the number of r's in strawberry.

There are many research papers on models using characters directly. One challenge is that effective context length is smaller.

ramon156• 13 hours ago

Doesn't really explain why its faster. "Optimizing for every kind of CPU" is not really enough info.

Cool project nonetheless, I will go through the code later tomorrow

Gigatoken: Fastest Tokenizer

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