_batch_encode_plus() got an unexpected keyword argument 'is_pretokenized' using BertTokenizerFast
### System Info

```shell
tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased')
for token, label in zip(tokenizer.convert_ids_to_tokens(training_set[0]["input_ids"]), training_set[0]["labels"]):
  print('{0:10}  {1}'.format(token, label))

The error I am getting is:
Traceback (most recent call last):
  File "C:\Users\1632613\Documents\Anit\NER_Trans\test.py", line 108, in <module>
    for token, label in zip(tokenizer.convert_ids_to_tokens(training_set[0]["input_ids"]), training_set[0]["labels"]):
  File "C:\Users\1632613\Documents\Anit\NER_Trans\test.py", line 66, in __getitem__
    encoding = self.tokenizer(sentence,
  File "C:\Users\1632613\AppData\Local\conda\conda\envs\ner\lib\site-packages\transformers\tokenization_utils_base.py", line 2477, in __call__
    return self.batch_encode_plus(
  File "C:\Users\1632613\AppData\Local\conda\conda\envs\ner\lib\site-packages\transformers\tokenization_utils_base.py", line 2668, in batch_encode_plus
    return self._batch_encode_plus(
TypeError: _batch_encode_plus() got an unexpected keyword argument 'is_pretokenized'
```


### Who can help?

@SaulLu 

### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

1. Download the NER Dataset from the Kaggle link (https://www.kaggle.com/datasets/namanj27/ner-dataset)
2. Use the Script with the mentioned versions of transformers and tokenizers:
tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased')
for token, label in zip(tokenizer.convert_ids_to_tokens(training_set[0]["input_ids"]), training_set[0]["labels"]):
  print('{0:10}  {1}'.format(token, label))


### Expected behavior

```shell
I expect to get the token, label from the script above.

Python Version: 3.9
tokenizers-0.12.1 
transformers-4.19.2

Anyone can shed some light please?
```

Hi @anitchakraborty ,

Could you share an example of `training_set[0]["input_ids"]`. I don't see "input_ids" in the columns of the kaggle dataset you shared - which are "Sentence #", "Word", "POS" and "Tag". Without a toy example, we can't reproduce your problem and it's hard for us to help you.<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.<|||||>I'm closing this issue due to lack of activity, but don't hesitate to come back to us with an extract of your data so that we can help you! :blush: <|||||>I am encountering the same issue, suggestions?<|||||>Hi @ludwigwittgenstein2 , 

Thank you for sharing that you also have this issue too. To understand what is going on, could you please share a code snippet that reproduces the error and the output of `transformers-cli env` ? Thanks in advance!<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.<|||||>I am having the same problem

here is the output of `transformers-cli env`

```
- `transformers` version: 4.25.1
- Platform: Linux-5.10.133+-x86_64-with-glibc2.27
- Python version: 3.8.16
- Huggingface_hub version: 0.11.1
- PyTorch version (GPU?): 1.13.0+cu116 (True)
- Tensorflow version (GPU?): 2.9.2 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
```

you can also find the colab notebook [here](https://drive.google.com/file/d/1HyTLxHs8S4tAsdpF4GHd34tKuVorBNOz/view?usp=sharing) <|||||>Experiencing the same issue. I think it depends on the version compatibility of PyTorch or Transformers. This notebook is different from the others since the predictions are made sentence-wise.

It works very well with Python 3.7, Transformers 3.0.2. @SaulLu would appreciate your help. <|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.<|||||>```
from transformers import BertTokenizerFast, EncoderDecoderModel
import torch
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
tokenizer = BertTokenizerFast.from_pretrained('mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization')
model = EncoderDecoderModel.from_pretrained('mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization').to(device)

def generate_summary(text):
    # cut off at BERT max length 512
    inputs = tokenizer([text], padding="max_length", truncation=True, max_new_tokens=512, return_tensors="pt")
    input_ids = inputs.input_ids.to(device)
    attention_mask = inputs.attention_mask.to(device)

    output = model.generate(input_ids, attention_mask=attention_mask)

    return tokenizer.decode(output[0], skip_special_tokens=True)
  
text = "your text to be summarized here..."
generate_summary(text)
```
**TypeError: PreTrainedTokenizerFast._batch_encode_plus() got an unexpected keyword argument 'max_new_tokens'**



