BertJapanese

Overview

The BERT models trained on Japanese text.

There are models with two different tokenization methods:

To use MecabTokenizer, you should pip install transformers["ja"] (or pip install -e .["ja"] if you install from source) to install dependencies.

See details on cl-tohoku repository.

Example of using a model with MeCab and WordPiece tokenization:

>>> import torch
>>> from transformers import AutoModel, AutoTokenizer

>>> bertjapanese = AutoModel.from_pretrained("cl-tohoku/bert-base-japanese")
>>> tokenizer = AutoTokenizer.from_pretrained("cl-tohoku/bert-base-japanese")

>>> ## Input Japanese Text
>>> line = "吾輩は猫である。"

>>> inputs = tokenizer(line, return_tensors="pt")

>>> print(tokenizer.decode(inputs["input_ids"][0]))
[CLS] 吾輩 は 猫 で ある 。 [SEP]

>>> outputs = bertjapanese(**inputs)

Example of using a model with Character tokenization:

>>> bertjapanese = AutoModel.from_pretrained("cl-tohoku/bert-base-japanese-char")
>>> tokenizer = AutoTokenizer.from_pretrained("cl-tohoku/bert-base-japanese-char")

>>> ## Input Japanese Text
>>> line = "吾輩は猫である。"

>>> inputs = tokenizer(line, return_tensors="pt")

>>> print(tokenizer.decode(inputs["input_ids"][0]))
[CLS] 吾 輩 は 猫 で あ る 。 [SEP]

>>> outputs = bertjapanese(**inputs)

Tips:

This model was contributed by cl-tohoku.

BertJapaneseTokenizer

class transformers.BertJapaneseTokenizer

< >

( vocab_file do_lower_case = False do_word_tokenize = True do_subword_tokenize = True word_tokenizer_type = 'basic' subword_tokenizer_type = 'wordpiece' never_split = None unk_token = '[UNK]' sep_token = '[SEP]' pad_token = '[PAD]' cls_token = '[CLS]' mask_token = '[MASK]' mecab_kwargs = None sudachi_kwargs = None jumanpp_kwargs = None **kwargs )

Parameters

  • vocab_file (str) — Path to a one-wordpiece-per-line vocabulary file.
  • do_lower_case (bool, optional, defaults to True) — Whether to lower case the input. Only has an effect when do_basic_tokenize=True.
  • do_word_tokenize (bool, optional, defaults to True) — Whether to do word tokenization.
  • do_subword_tokenize (bool, optional, defaults to True) — Whether to do subword tokenization.
  • word_tokenizer_type (str, optional, defaults to "basic") — Type of word tokenizer. Choose from [“basic”, “mecab”, “sudachi”, “jumanpp”].
  • subword_tokenizer_type (str, optional, defaults to "wordpiece") — Type of subword tokenizer. Choose from [“wordpiece”, “character”].
  • mecab_kwargs (dict, optional) — Dictionary passed to the MecabTokenizer constructor.
  • sudachi_kwargs (dict, optional) — Dictionary passed to the SudachiTokenizer constructor.
  • jumanpp_kwargs (dict, optional) — Dictionary passed to the JumanppTokenizer constructor.

Construct a BERT tokenizer for Japanese text.