TypeError: EncDecRNNTBPEModel.change_vocabulary() got an unexpected keyword argument 'new_vocabulary'
Actually no one of the new models has new_vocabulary argument.
You need to use "change_vocabulary" method

```
char_model.change_vocabulary(
        new_tokenizer_dir="your_tokenized_folder",
        new_tokenizer_type="bpe"
    )

```

You may receive "your_tokenized_folder" whit the help of script/process_asr_text_tokenizer.py

`python process_asr_text_tokenizer.py --data_file=your_plain_text --data_root="your_tokenized_folder" --vocab_size=42 --tokenizer="wpe" --log
`

Dear Team,

I am getting this error message, while I am trying to train EncDecRNNTBPEModel model.
Meanwhile the code is Ok with other models, for example with  stt_en_quartznet15x5.  

`TypeError: EncDecRNNTBPEModel.change_vocabulary() got an unexpected keyword argument 'new_vocabulary'
`

**Describe the bug**

```
char_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained(model_name="stt_en_conformer_transducer_xlarge", map_location='cpu')
char_model.change_vocabulary(new_vocabulary=list(train_set))

```

Thank you in advance!

**Steps/Code to reproduce bug**

Please list *minimal* steps or code snippet for us to be able to reproduce the bug.

A  helpful guide on on how to craft a minimal bug report  http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports. 


**Expected behavior**

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