Multilingual Issue
Dear authors,
I have two questions.

First, how can I use multilingual pre-trained BERT in pytorch?
Is it all download model to $BERT_BASE_DIR?

Second is tokenization issue.
For Chinese and Japanese, tokenizer may works, however, for Korean, it shows different result that I expected

```
import torch
from pytorch_pretrained_bert import BertTokenizer, BertModel, BertForMaskedLM
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
text = "안녕하세요"
tokenized_text = tokenizer.tokenize(text)
print(tokenized_text)
```
` ['ᄋ', '##ᅡ', '##ᆫ', '##ᄂ', '##ᅧ', '##ᆼ', '##ᄒ', '##ᅡ', '##ᄉ', '##ᅦ', '##ᄋ', '##ᅭ']

The result is based on not 'character' but 'byte-based character'
May it comes from unicode issue. (I expect ['안녕', '##하세요'])

Hi, you can use the multilingual model as [indicated in the readme](https://github.com/huggingface/pytorch-pretrained-BERT#loading-google-ais-pre-trained-weigths-and-pytorch-dump) with the commands:
```python
tokenizer = BertTokenizer.from_pretrained('bert-base-multilingual')
model = BertModel.from_pretrained('bert-base-multilingual')
````
This will load the multilingual vocabulary (which should contain korean) that your command was not loading.