I recently tested on the below code based on the source: https://github.com/cl-tohoku/bert-japanese/blob/master/masked_lm_example.ipynb
import torch
from transformers.tokenization_bert_japanese import BertJapaneseTokenizer
from transformers.modeling_bert import BertForMaskedLM
tokenizer = BertJapaneseTokenizer.from_pretrained('cl-tohoku/bert-base-japanese-whole-word-masking')
model = BertForMaskedLM.from_pretrained('cl-tohoku/bert-base-japanese-whole-word-masking')
input_ids = tokenizer.encode(f'''
青葉山で{tokenizer.mask_token}の研究をしています。
''', return_tensors='pt')
when i try to encode it, I received error such as:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-29-f8582275f4db> in <module>
1 input_ids = tokenizer.encode(f'''
2 青葉山で{tokenizer.mask_token}の研究をしています。
----> 3 ''', return_tensors='pt')
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_utils_base.py in encode(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, return_tensors, **kwargs)
1428 stride=stride,
1429 return_tensors=return_tensors,
-> 1430 **kwargs,
1431 )
1432
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_utils_base.py in encode_plus(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_pretokenized, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
1740 return_length=return_length,
1741 verbose=verbose,
-> 1742 **kwargs,
1743 )
1744
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_utils.py in _encode_plus(self, text, text_pair, add_special_tokens, padding_strategy, truncation_strategy, max_length, stride, is_pretokenized, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
452 )
453
--> 454 first_ids = get_input_ids(text)
455 second_ids = get_input_ids(text_pair) if text_pair is not None else None
456
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_utils.py in get_input_ids(text)
423 def get_input_ids(text):
424 if isinstance(text, str):
--> 425 tokens = self.tokenize(text, **kwargs)
426 return self.convert_tokens_to_ids(tokens)
427 elif isinstance(text, (list, tuple)) and len(text) > 0 and isinstance(text[0], str):
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_utils.py in tokenize(self, text, **kwargs)
362
363 no_split_token = self.unique_no_split_tokens
--> 364 tokenized_text = split_on_tokens(no_split_token, text)
365 return tokenized_text
366
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_utils.py in split_on_tokens(tok_list, text)
356 (
357 self._tokenize(token) if token not in self.unique_no_split_tokens else [token]
--> 358 for token in tokenized_text
359 )
360 )
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_utils.py in <genexpr>(.0)
356 (
357 self._tokenize(token) if token not in self.unique_no_split_tokens else [token]
--> 358 for token in tokenized_text
359 )
360 )
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_bert_japanese.py in _tokenize(self, text)
153 def _tokenize(self, text):
154 if self.do_word_tokenize:
--> 155 tokens = self.word_tokenizer.tokenize(text, never_split=self.all_special_tokens)
156 else:
157 tokens = [text]
~/.pyenv/versions/3.7.0/envs/personal/lib/python3.7/site-packages/transformers/tokenization_bert_japanese.py in tokenize(self, text, never_split, **kwargs)
205 break
206
--> 207 token, _ = line.split("\t")
208 token_start = text.index(token, cursor)
209 token_end = token_start + len(token)
ValueError: too many values to unpack (expected 2)
Does anyone experienced this before? I tried a lot of different ways and refer to many posts but all using the same methods and no explanations, I just wanted to test multiple languages, other languages seem to work fine but not with japanese and I dont know why.
NOTE: Shortly after this question I released a version of IPADic that works with the latest versions of mecab-python3. You should be able to fix things by installing transformers[ja], which will install the main dictionaries used with HuggingFace models.
I'm the mecab-python3 maintainer. Transformers relies on the bundled dictionary in versions prior to 1.0, which has been removed because it's old. I will be adding it as an option in a release soon, but in the meantime you can install an old version.
The command posted by vivasra doesn't work because it specifies a version of a different package (notice there's no "3" in the package name) that doesn't exist. You can use this:
pip install mecab-python3=0.996.5
If you still have trouble please open an issue on Github.