Add link to new comunity notebook (optimization)
related to https://github.com/huggingface/transformers/issues/4842#event-3469184635

This notebook is about benchmarking model training with/without dynamic padding optimization. 
https://github.com/ELS-RD/transformers-notebook 

Using dynamic padding on MNLI provides a **4.7 times training time reduction**, with max pad length set to 512. The effect is strong because few examples are >> 400 tokens in this dataset. IRL, it will depend of the dataset, but it always bring improvement and, after more than 20 experiments listed in this [article](https://towardsdatascience.com/divide-hugging-face-transformers-training-time-by-2-or-more-21bf7129db9q-21bf7129db9e?source=friends_link&sk=10a45a0ace94b3255643d81b6475f409), it seems to not hurt performance.

Following advice from @patrickvonplaten I do the PR myself :-)
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5195?src=pr&el=h1) Report
> Merging [#5195](https://codecov.io/gh/huggingface/transformers/pull/5195?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1c5cd8e5f59154905c5ae0f47a8c8905618a12ff&el=desc) will **increase** coverage by `0.01%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5195/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5195?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5195      +/-   ##
==========================================
+ Coverage   77.98%   78.00%   +0.01%     
==========================================
  Files         138      138              
  Lines       23786    23786              
==========================================
+ Hits        18550    18554       +4     
+ Misses       5236     5232       -4     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5195?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5195/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `91.18% <0.00%> (-0.13%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5195/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.00% <0.00%> (ø)` | |
| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/5195/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.57% <0.00%> (+1.18%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5195?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5195?src=pr&el=footer). Last update [1c5cd8e...438d62f](https://codecov.io/gh/huggingface/transformers/pull/5195?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
<|||||>That's really a great notebook and fits very well with what we are currently working on I think @mfuntowicz 