Add TF2 NER example
Author: jplu
Pull request: yes

Hi,

Here my small contribution. I have implemented the TF2 version of the NER example already existing in the repo. I tried to have an implementation as close as possible of the Pytorch version.

Let me know for any needed changes :)

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1940?src=pr&el=h1) Report
> Merging [#1940](https://codecov.io/gh/huggingface/transformers/pull/1940?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/88b317739fe56888528c857fc8e90967148a0051?src=pr&el=desc) will **decrease** coverage by `1.04%`.
> The diff coverage is `51.37%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/1940/graphs/tree.svg?width=650&token=9qOlN6Hb1c&height=150&src=pr)](https://codecov.io/gh/huggingface/transformers/pull/1940?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #1940      +/-   ##
==========================================
- Coverage   84.26%   83.21%   -1.05%     
==========================================
  Files         104      106       +2     
  Lines       15431    15679     +248     
==========================================
+ Hits        13003    13048      +45     
- Misses       2428     2631     +203
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1940?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [transformers/tokenization\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rva2VuaXphdGlvbl9kaXN0aWxiZXJ0LnB5) | `100% <ø> (ø)` | :arrow_up: |
| [transformers/modeling\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2Rpc3RpbGJlcnQucHk=) | `95.87% <ø> (ø)` | :arrow_up: |
| [transformers/configuration\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbmZpZ3VyYXRpb25fZGlzdGlsYmVydC5weQ==) | `89.74% <ø> (ø)` | :arrow_up: |
| [transformers/modeling\_tf\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX2F1dG8ucHk=) | `32.5% <ø> (-18.75%)` | :arrow_down: |
| [transformers/modeling\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2F1dG8ucHk=) | `31.11% <0%> (-0.71%)` | :arrow_down: |
| [transformers/modeling\_tf\_pytorch\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3B5dG9yY2hfdXRpbHMucHk=) | `95.13% <0%> (+2.18%)` | :arrow_up: |
| [transformers/modeling\_tf\_transfo\_xl\_utilities.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3RyYW5zZm9feGxfdXRpbGl0aWVzLnB5) | `85.57% <100%> (ø)` | :arrow_up: |
| [transformers/modeling\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3V0aWxzLnB5) | `90.86% <100%> (+1.42%)` | :arrow_up: |
| [transformers/configuration\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL2NvbmZpZ3VyYXRpb25fdXRpbHMucHk=) | `88.31% <100%> (-3.8%)` | :arrow_down: |
| [transformers/modeling\_tf\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX29wZW5haS5weQ==) | `95.92% <100%> (ø)` | :arrow_up: |
| ... and [38 more](https://codecov.io/gh/huggingface/transformers/pull/1940/diff?src=pr&el=tree-more) | |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/1940?src=pr&el=continue).
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> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1940?src=pr&el=footer). Last update [88b3177...938da1c](https://codecov.io/gh/huggingface/transformers/pull/1940?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


I finished to implement the TF2 NER, it should be really similar to the Pytorch one as I tried to reproduce most of the parameters.

Thanks for your contribution @jplu 

Do you mind doing a clean rebase (and force-push to this branch), or create a new PR, with just your changes?

I will remake the PR, that will be cleaner :)