Gigatoken: Fastest Tokenizer

Gigatoken: Fastest Tokenizer(twitter.com)

26 points by convexstrictly 47 days ago | 5 comments

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

Alifatisk 47 days ago | |

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

benj111 47 days 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?

convexstrictly 47 days 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 47 days 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