python313-tokenizers

Provides an implementation of today's most used tokenizers

Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. * Train new vocabularies and tokenize, using today's most used tokenizers. * Extremely fast (both training and tokenization), thanks to the Rust implementation. Takes less than 20 seconds to tokenize a GB of text on a server's CPU. * Easy to use, but also extremely versatile. * Designed for research and production. * Normalization comes with alignments tracking. It's always possible to get the part of the original sentence that corresponds to a given token. * Does all the pre-processing: Truncate, Pad, add the special tokens your model needs.

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