Add XLM-RoBERTa model for TF2
Hello,

I have implemented the XLM-RoBERTa model handling for Tensorflow 2.
There is a little incompatibility between isort and black apparently https://github.com/psf/black/issues/251<|||||># [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=h1) Report
> Merging [#2454](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9d87eafd118739a4c121d69d7cff425264f01e1c?src=pr&el=desc) will **increase** coverage by `0.6%`.
> The diff coverage is `100%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/2454/graphs/tree.svg?width=650&token=9qOlN6Hb1c&height=150&src=pr)](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=tree)

```diff
@@            Coverage Diff            @@
##           master    #2454     +/-   ##
=========================================
+ Coverage   74.51%   75.11%   +0.6%     
=========================================
  Files          87       88      +1     
  Lines       14920    14945     +25     
=========================================
+ Hits        11117    11226    +109     
+ Misses       3803     3719     -84
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/\_\_init\_\_.py](https://codecov.io/gh/huggingface/transformers/pull/2454/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `98.8% <100%> (+0.01%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_xlm\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/2454/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG1fcm9iZXJ0YS5weQ==) | `100% <100%> (ø)` | |
| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/2454/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `56.72% <0%> (+27.54%)` | :arrow_up: |

------

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> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=footer). Last update [9d87eaf...bb1aa06](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
<|||||>does it work even if xlm-roberta-large is pretrained pytorch model? i mean do we need to convert pytorch model to tensorflow?<|||||>@jplu I took the liberty of updating the documentation to the new format directly on your fork. Thank you for your contribution, this is awesome!