wip/py-tokenizers 0.22.1 NetBSD

Provides an implementation of today's most used tokenizers, with a focus on performance and versatility.

Bindings over the Rust implementation. If you are interested in the High-level design, you can go check it there.

Main features:

* Train new vocabularies and tokenize using 4 pre-made tokenizers (Bert WordPiece and the 3 most common BPE versions). * 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.