Language modelling head has zero weights in pretrained TFMobileBertForMaskedLM
## Description
The `TFMobileBertForMaskedLM` example returns all zero logits while `MobileBertForMaskedLM` example works fine.
https://huggingface.co/transformers/model_doc/mobilebert.html#tfmobilebertformaskedlm

I checked language modeling head weights for both models and found that TF pretrained model has zero weights.

## 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: 4.3.0
- Platform: Google Colab
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101
- Tensorflow version (GPU?): 2.4.1
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

### Who can help
@jplu @patrickvonplaten

## Information

Model I am using (Bert, XLNet ...): TFMobileBertForMaskedLM

The problem arises when using:
- [x] the official example scripts: (give details below)

## To reproduce

```
from transformers import MobileBertForMaskedLM
from transformers import TFMobileBertForMaskedLM

# PyTorch
model = MobileBertForMaskedLM.from_pretrained('google/mobilebert-uncased')
print(list(model.cls.parameters())[0])

# Parameter containing:
# tensor([-7.2946, -7.4302, -7.5401,  ..., -7.4850, -7.4503, -2.7798],
#       requires_grad=True)

# TensorFlow
model = TFMobileBertForMaskedLM.from_pretrained('google/mobilebert-uncased')
print(model.layers[1].get_weights()[0])

# array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)
```
## Expected behavior
Language modeling head for TFMobileBertForMaskedLM should have the same weights as of MobileBertForMaskedLM

Hello!

Indeed there is an issue in the naming for `TFMobileBertForMaskedLM`. This will be fixed in the next release.<|||||>OK, thanks for the quick response!<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.