TL;DR: Hugging Face, the NLP research company known for its transformers library (DISCLAIMER: I work at Hugging Face), has just released a new open-source libra

TL;DR: Hugging Face, the NLP research company known for its transformers library (DISCLAIMER: I work at Hugging Face), has just released a new open-source library for ultra-fast & versatile tokenization for NLP neural net models (i.e. converting strings in model input tensors). Main features: - Encode 1GB in 20sec - Provide BPE/Byte-Level-BPE/WordPiece/SentencePiece... - Compute exhaustive set of outputs (offset mappings, attention masks, special token masks...) - Written in Rust with bindings for Python and node.js Github repository and doc: https://github.com/huggingface/tokenizers/tree/master/tokenizers https://github.com/huggingface/tokenizers/tree/master/tokeni... To install: - Rust: https://crates.io/crates/tokenizers https://crates.io/crates/tokenizers - Python: pip install tokenizers - Node: npm install tokenizers