DeBERTa v2 throws "TypeError: stat: path should be string...", v1 not
Author: 205g0
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.3.1
- Platform: Linux-5.4.0-54-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1+cpu (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: false
- Using distributed or parallel set-up in script?: false

### Who can help

@BigBird01 @patil-suraj 

## Information

Model I am using (DeBERTa v2):

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. Create this file:
```
from transformers import AutoTokenizer, AutoModel
import torch

tokenizer = AutoTokenizer.from_pretrained('microsoft/deberta-xlarge-v2')
model = AutoModel.from_pretrained('microsoft/deberta-xlarge-v2')

inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
outputs = model(**inputs)

last_hidden_states = outputs.last_hidden_state
print(outputs)
```

2. Run the file

3. You'll get:
```
(venv) root@16gb:~/deberta# python3 index.py
Traceback (most recent call last):
  File "index.py", line 4, in <module>
    tokenizer = AutoTokenizer.from_pretrained('microsoft/deberta-xlarge-v2')
  File "/root/deberta/venv/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py", line 398, in from_pretrained
    return tokenizer_class_py.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
  File "/root/deberta/venv/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1788, in from_pretrained
    return cls._from_pretrained(
  File "/root/deberta/venv/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1860, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "/root/deberta/venv/lib/python3.8/site-packages/transformers/models/deberta/tokenization_deberta.py", line 542, in __init__
    if not os.path.isfile(vocab_file):
  File "/usr/lib/python3.8/genericpath.py", line 30, in isfile
    st = os.stat(path)
TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType
```

I tried this with the DeBERTa v1 models and there was no error. I've the same behavior when using `DebertaTokenizer, DebertaModel`

## Expected behavior

No error.

Comments:
Hi @205g0 

Thank you for reporting this! 

`microsoft/deberta-xlarge-v2` uses `sentencepiece` vocab and it's not implemented for deberta, which is the reason for this error. 

Hey Suraj, thanks for the quick response and good to know!

@BigBird01  do you think you could add the missing tokenizer, otherwise, I could add it. Thanks!

DeBERTa-v2 is not available in the library yet. We're working towards it with @BigBird01.

Thanks @205g0  for the interest in DeBERTa-v2. We are working on it with @LysandreJik, hopefully, it will be available soon.  You can check our [PR](https://github.com/huggingface/transformers/pull/10018) for the progress.

Oh sorry, @BigBird01, I did not realize that this was a work in progress

> Oh sorry, @BigBird01, I did not realize that this was a work in progress

No worry, @patil-suraj. Thanks for your quick response. We are glad to integrate these SOTA NLU models with HF to benefit the community:) 

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