rust_tokenizers 8.1.1

High performance tokenizers for Rust
Documentation 
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// Copyright 2019 Guillaume Becquin
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//     http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

//!# Vocabularies
//!
//! This module contains the vocabularies leveraged by the tokenizer. These contain methods for
//! deserialization of vocabulary files and access by the tokenizers, including:
//! - dictionaries (mapping from token to token ids)
//! - merge files (used by Byte-Pair Encoding tokenizers)
//! - sentence-piece models (trie structure and methods to find common prefix subtokens)
//!
//! The following vocabularies have been implemented:
//! - BERT
//! - ALBERT
//! - GPT2
//! - GPT
//! - Marian
//! - RoBERTa
//! - T5
//! - XLMRoBERTa
//! - XLNet
//! - SentencePiece
//!
//! All vocabularies implement the `Vocab` trait exposing a standard interface for integration with
//! the tokenizers.

mod albert_vocab;
pub(crate) mod base_vocab;
mod bert_vocab;
pub(crate) mod bpe_vocab;
mod deberta_v2_vocab;
mod deberta_vocab;
mod fnet_vocab;
mod gpt2_vocab;
mod m2m100_vocab;
mod marian_vocab;
mod mbart50_vocab;
mod nllb_vocab;
mod openai_gpt_vocab;
mod pegasus_vocab;
mod prophetnet_vocab;
mod reformer_vocab;
mod roberta_vocab;
mod sentence_piece_bpe_model;
mod sentence_piece_unigram_model;
mod sentence_piece_vocab;
pub(crate) mod sentencepiece_proto;
mod t5_vocab;
mod xlm_roberta_vocab;
mod xlnet_vocab;

pub use albert_vocab::AlbertVocab;
pub use base_vocab::{BaseVocab, Vocab};
pub use bert_vocab::BertVocab;
pub use bpe_vocab::{BpePairRef, BpePairVocab};
pub use deberta_v2_vocab::DeBERTaV2Vocab;
pub use deberta_vocab::DeBERTaVocab;
pub use fnet_vocab::FNetVocab;
pub use gpt2_vocab::Gpt2Vocab;
pub use m2m100_vocab::M2M100Vocab;
pub use marian_vocab::MarianVocab;
pub use mbart50_vocab::MBart50Vocab;
pub use nllb_vocab::NLLBVocab;
pub(crate) use nllb_vocab::EXTENDED_FAIRSEQ_LANGUAGE_CODES;
pub use openai_gpt_vocab::OpenAiGptVocab;
pub use pegasus_vocab::PegasusVocab;
pub use prophetnet_vocab::ProphetNetVocab;
pub use reformer_vocab::ReformerVocab;
pub use roberta_vocab::RobertaVocab;
pub use sentence_piece_bpe_model::SentencePieceBpeModel;
pub use sentence_piece_unigram_model::SentencePieceModel;
pub use sentence_piece_vocab::SentencePieceVocab;
pub use t5_vocab::T5Vocab;
pub use xlm_roberta_vocab::XLMRobertaVocab;
pub use xlnet_vocab::XLNetVocab;