

TITLE
Tokenizer not working

COMMENTS
12

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## Environment info

- `transformers` version: 4.3.2
- Platform: Ubuntu 16.04.6 LTS
- Python version: 3.8.8

### Who can help

- tokenizers: @n1t0, @LysandreJik


## Information

To reproduce:

```
conda create --name=env1 python=3.8 jupyter transformers tokenizers -y -c conda-forge
conda activate env1
```
```
~$ python
Python 3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) 
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from transformers import AutoTokenizer
None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.
>>> tokenizer = AutoTokenizer.from_pretrained("bert-base-cased", do_lower_case=False, strip_accents=False)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/guillem.garcia/.conda/envs/cosas/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py", line 395, in from_pretrained
    return tokenizer_class_fast.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
  File "/home/guillem.garcia/.conda/envs/cosas/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1788, in from_pretrained
    return cls._from_pretrained(
  File "/home/guillem.garcia/.conda/envs/cosas/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1860, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "/home/guillem.garcia/.conda/envs/cosas/lib/python3.8/site-packages/transformers/models/bert/tokenization_bert_fast.py", line 199, in __init__
    self.backend_tokenizer.normalizer = pre_tok_class(**pre_tok_state)
TypeError: PyBertNormalizer.__new__() got an unexpected keyword argument: do_lower_case
```
The most weird thing is that running that exact command in a jupyter notebook does not raise any error. Also `AutoTokenizer.from_pretrained("bert-base-cased", do_lower_case=False)` works so it seems to be something related to strip accents.
