rust-tokenizers

Rust-tokenizer is a drop-in replacement for the tokenization methods from the Transformers library It includes a broad range of tokenizers for state-of-the-art transformers architectures, including:

• Sentence Piece (unigram model)
• Sentence Piece (BPE model)
• BERT
• ALBERT
• DistilBERT
• RoBERTa
• GPT
• GPT2
• ProphetNet
• CTRL
• Pegasus
• MBart50
• M2M100
• NLLB
• DeBERTa
• DeBERTa (v2)

The wordpiece based tokenizers include both single-threaded and multi-threaded processing. The Byte-Pair-Encoding tokenizers favor the use of a shared cache and are only available as single-threaded tokenizers Using the tokenizers requires downloading manually the tokenizers required files (vocabulary or merge files). These can be found in the Transformers library.

Usage example

use std::path::PathBuf;

use rust_tokenizers::tokenizer::{BertTokenizer, Tokenizer, TruncationStrategy};
use rust_tokenizers::vocab::{BertVocab, Vocab};

let lowercase: bool = true;
let strip_accents: bool = true;
let vocab_path: PathBuf  = PathBuf::from("path/to/vocab");
let vocab: BertVocab = BertVocab::from_file(&vocab_path)?;
let test_sentence: Example = Example::new_from_string("This is a sample sentence to be tokenized");
let bert_tokenizer: BertTokenizer = BertTokenizer::from_existing_vocab(vocab, lowercase, strip_accents);

println!("{:?}", bert_tokenizer.encode(&test_sentence.sentence_1,
                                       None,
                                       128,
                                       &TruncationStrategy::LongestFirst,
                                       0));