Pre-Trained Model (ipuneetrathore/bert-base-cased-finetuned-finBERT) loads in PyTorch but not Tensorflow
Author: turmeric-blend
Pull request: no

# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): TFBertModel

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)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [X] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

This Works:
```
import torch
PRE_TRAINED_MODEL_NAME = 'ipuneetrathore/bert-base-cased-finetuned-finBERT'
model = BertForSequenceClassification.from_pretrained(PRE_TRAINED_MODEL_NAME)

# loads just fine
```

This Does NOT Work:
```
import tensorflow as tf
PRE_TRAINED_MODEL_NAME = 'ipuneetrathore/bert-base-cased-finetuned-finBERT'
model = TFBertForSequenceClassification.from_pretrained(PRE_TRAINED_MODEL_NAME)

# ERROR:

OSError: Can't load weights for 'ipuneetrathore/bert-base-cased-finetuned-finBERT'. Make sure that:

- 'ipuneetrathore/bert-base-cased-finetuned-finBERT' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'ipuneetrathore/bert-base-cased-finetuned-finBERT' is the correct path to a directory containing a file named one of tf_model.h5, pytorch_model.bin.
```

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## Expected behavior

It should load the model.

<!-- A clear and concise description of what you would expect to happen. -->

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.0.0
- Platform: Ubuntu 18.04
- Python version: 3.7
- PyTorch version (GPU?): 1.3.1 with GPU
- Tensorflow version (GPU?): 2.1.0 with GPU
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No


Comments:
Hello! That's because the user that uploaded that model didn't upload a TensorFlow version, only a PyTorch version. You can see it when you click on "show all files", you'll see that there is a `pytorch_model.bin`, but no `tf_model.h5`.

Here you can solve this by telling the TF model that you want to load from pytorch weights:

```py
import tensorflow as tf
PRE_TRAINED_MODEL_NAME = 'ipuneetrathore/bert-base-cased-finetuned-finBERT'
model = TFBertForSequenceClassification.from_pretrained(PRE_TRAINED_MODEL_NAME, from_pt=True)  # <-- here
```

and you could also ask the author (I believe @ipuneetrathore) if they could upload a TF version of the weights

hi @julien-c just wondering if there are any difference if the pytorch weights could be loaded through TF model anyway?

Just that the PyTorch weights will have to be converted on the fly every time you instantiate your TF model