TypeError while loading the model built from scratch using transformer 
# 🐛 Bug

> TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType`

 ---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)
<ipython-input-33-cd040b700e71> in <module>()
      3 from transformers import BertTokenizer, AdamW, BertForNextSentencePrediction
      4 
----> 5 tokenizer = BertTokenizer.from_pretrained('/content/drive/My Drive/Colab Notebooks/data/test/')

3 frames
/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils.py in from_pretrained(cls, *inputs, **kwargs)
    391 
    392         """
--> 393         return cls._from_pretrained(*inputs, **kwargs)
    394 
    395     @classmethod

/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils.py in _from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs)
    542         # Instantiate tokenizer.
    543         try:
--> 544             tokenizer = cls(*init_inputs, **init_kwargs)
    545         except OSError:
    546             raise OSError(

/usr/local/lib/python3.6/dist-packages/transformers/tokenization_bert.py in __init__(self, vocab_file, do_lower_case, do_basic_tokenize, never_split, unk_token, sep_token, pad_token, cls_token, mask_token, tokenize_chinese_chars, **kwargs)
    186         self.max_len_sentences_pair = self.max_len - 3  # take into account special tokens
    187 
--> 188         if not os.path.isfile(vocab_file):
    189             raise ValueError(
    190                 "Can't find a vocabulary file at path '{}'. To load the vocabulary from a Google pretrained "

/usr/lib/python3.6/genericpath.py in isfile(path)
     28     """Test whether a path is a regular file"""
     29     try:
---> 30         st = os.stat(path)
     31     except OSError:
     32         return False

TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType

## Information
I am trying to fine-tune the model that I built from scratch using transformers. When I am trying to load the tokenizer from the model that is just made, it is giving Type Error
Model I am using (Bert, XLNet ...): Model is built from scratch using https://huggingface.co/blog/how-to-train 



Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
```
import torch
import transformers
from transformers import BertTokenizer, AdamW, BertForNextSentencePrediction

tokenizer = BertTokenizer.from_pretrained('/content/drive/My Drive/Colab Notebooks/data/model/')

```
The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)


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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

## Environment info
<!-- You can run the command `python transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version:
- Platform: Google Colab
- Python version: 3.x
- PyTorch version (GPU?):'1.4.0'
- Tensorflow version (GPU?):'2.8.0'
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

looks like it's not able to find vocabulary file. Make sure there is a vocab.txt file for bert. Otherwise, you can simply load it by `tokenizer = BertTokenizer(vocab_file="path to vocab", and configs)`.<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
