XLNet for Token classification
Author: alexzubiaga
Pull request: yes

Hi,

this PR adds a XLNet based token classifier for PyTorch `XLNetForTokenClassification` and TensorFlow `TFXLNetForTokenClassification` with unit test that allows performing sequence labeling tasks like NER or PoS tagging.


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1870?src=pr&el=h1) Report
> Merging [#1870](https://codecov.io/gh/huggingface/transformers/pull/1870?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f3386d938348628c91457fc7d8650c223317a053?src=pr&el=desc) will **increase** coverage by `1.37%`.
> The diff coverage is `88.4%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/1870/graphs/tree.svg?width=650&token=9qOlN6Hb1c&height=150&src=pr)](https://codecov.io/gh/huggingface/transformers/pull/1870?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #1870      +/-   ##
==========================================
+ Coverage   82.72%   84.09%   +1.37%     
==========================================
  Files          97       97              
  Lines       14316    14383      +67     
==========================================
+ Hits        11843    12096     +253     
+ Misses       2473     2287     -186
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/1870?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [transformers/tests/modeling\_tf\_xlnet\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX3hsbmV0X3Rlc3QucHk=) | `96.05% <100%> (+0.3%)` | :arrow_up: |
| [transformers/modeling\_tf\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3hsbmV0LnB5) | `88.53% <100%> (+0.34%)` | :arrow_up: |
| [transformers/tests/modeling\_xlnet\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3hsbmV0X3Rlc3QucHk=) | `94.28% <81.81%> (-1.85%)` | :arrow_down: |
| [transformers/modeling\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3hsbmV0LnB5) | `73.95% <82.6%> (+2.77%)` | :arrow_up: |
| [transformers/modeling\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX29wZW5haS5weQ==) | `82% <0%> (+1.33%)` | :arrow_up: |
| [transformers/modeling\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX2N0cmwucHk=) | `96.46% <0%> (+2.21%)` | :arrow_up: |
| [transformers/modeling\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3JvYmVydGEucHk=) | `71.76% <0%> (+12.35%)` | :arrow_up: |
| [transformers/tests/modeling\_tf\_common\_test.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL3Rlc3RzL21vZGVsaW5nX3RmX2NvbW1vbl90ZXN0LnB5) | `97.08% <0%> (+15.53%)` | :arrow_up: |
| [transformers/modeling\_tf\_pytorch\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/1870/diff?src=pr&el=tree#diff-dHJhbnNmb3JtZXJzL21vZGVsaW5nX3RmX3B5dG9yY2hfdXRpbHMucHk=) | `92.95% <0%> (+83.09%)` | :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/1870?src=pr&el=footer). Last update [f3386d9...4193aa9](https://codecov.io/gh/huggingface/transformers/pull/1870?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


This looks good to me, thank you @alexzubiaga !

This is great, thanks a lot @alexzubiaga (and nice work adding the tests!).
Merging