Add method to directly load TF Checkpoints for Bert models
## Summary
In this PR, I changed some documentation, and added `from_tf_ckpt()` method to `BertPreTrainedModel`.

This method allows users to directly load TensorFlow checkpoints (e.g. `model.ckpt-XXXX` files) for a task specific Bert model like `BertForTokenClassification` or `BertForSequenceClassification`.

**For example:**
```python
model = BertForSequenceClassification.from_tf_ckpt("/path/to/bert/bert_config.json",
                                                   "/path/to/bert/model.ckpt-12000",
                                                   num_labels=num_labels)
```

## Why this is needed:
This functionality has been requested by a number of people, like #676, https://github.com/huggingface/pytorch-pretrained-BERT/issues/676#issuecomment-501778493, #580, https://github.com/huggingface/pytorch-pretrained-BERT/issues/580#issuecomment-497286535, https://github.com/huggingface/pytorch-pretrained-BERT/issues/438#issuecomment-479405364
Hi, I'm not convinced we need this additional option, see my [comment](https://github.com/huggingface/pytorch-pretrained-BERT/issues/676#issuecomment-502252962) in the associated issue thread.<|||||>As mentioned in, https://github.com/huggingface/pytorch-pretrained-BERT/issues/676#issuecomment-506134506, I recognise that directly loading TF checkpoints is a rather niche use case and will close this PR.<|||||>I don't think it's a niche but the `from_tf` option was there for importing from tf files so I would rather fix it to work in all cases rather than have several ways to import from a tf checkpoint.<|||||>I'll have a look.