Using HuggingFace pre-trained transformer to tokenize and generate iterator for a different text than the one it was trained on
Hello,
I am trying to do NLP by using HuggingFace transformers, and I have a question. Is it possible to use the pre-trained HuggingFace Transformer-XL and its pre-trained vocabulary to tokenize and generate BPTTIterator for the WikiText2 dataset instead of the WikiText103 that the transformer was originally trained on? If yes, could someone provide me example codes to illustrate how to 1.tokenize and 2. generate BPTTIterator to analyze the WikiText2, based on the pre-trained HuggingFace transformer XL model and its vocabulary?

NOTE: the WikiText2 can be obtained via

```js
import torchtext
# load WikiText-2 dataset and split it into train and test set
train_Wiki2, val_Wiki2, test_Wiki2 = torchtext.datasets.WikiText2.splits(TEXT)
```
or

```js
import lineflow as lf
import lineflow.datasets as lfds

# load WikiText-103 dataset
train_Wiki103 = lfds.WikiText2('train')
test_Wiki103 = lfds.WikiText2('test')
```

Thank you,
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