Add FastFormers to the example directory
# What does this PR do?

Add FastFormers into the example directory.
https://github.com/huggingface/transformers/issues/8083

https://arxiv.org/abs/2010.13382
https://github.com/microsoft/fastformers

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to the it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/master/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/master/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?
@JetRunner @LysandreJik 


Thanks, @JetRunner ! I will clean up the code and fix the CI checks.<|||||>Thanks for the opinions, @LysandreJik!

1. The onnx related files are necessary before it's merges into master branch of onnxruntime
2. I agree with you regarding the binary files. I can put the binary files in a different place and put a script to download them, here.
3. That sounds good. I will look at the dataset library to see how to utilize it.<|||||>That's great, thanks a lot @ykim362! I think we can do with the ONNX files while your PR is in waiting over at onnxruntime.<|||||>Thanks for the review @patrickvonplaten ! I can make changes most of them as you recommended.

Regarding `attention_head_size`, this is necessary for head pruned transformers. I can think of two ways to keep backward compatibility.
1. Create a new model class by subclassing `RoBERTa`. FastFormers supports BERT and RoBERTa, so that would work for both.
2. In the current BERT model, add a default behavior (same as current logic) when `attention_head_size` doesn't exist. Then, it could be used only when `attention_head_size` parameter exists in the config file.

Or, I am open to any suggestions. :)<|||||>What is the status with this project? Anything I can help with?<|||||>> What is the status with this project? Anything I can help with?

I think it's mostly about this: https://github.com/huggingface/transformers/pull/8637/files?file-filters%5B%5D=.png&file-filters%5B%5D=.py&file-filters%5B%5D=.whl#r545051113 -> in a first PR we should not touch this logic IMO<|||||>I am sorry, but I have been fully loaded with some other stuffs. I won't be able to make a progress. I'd like to close this to avoid any confusion.<|||||>Thank you for the clarification @ykim362, I hope we may still collaborate in the future!<|||||>Thanks, @LysandreJik ! Likewise for the future collaboration!  :)