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add exemplary training data. update to nvidia apex. refactor 'item -> line in doc' mapping. add warning for unknown word.

Adds an example for loading a pre-trained BERT model and fine tune it as a language model (masked tokens & nextSentence) on your target corpus.

I tried to address https://github.com/huggingface/pytorch-pretrained-BERT/issues/76
should be correct, but there's likely a more efficient way.