Parallelize LongT5
# What does this PR do?
Adds parallelization to LongT5

Fixes # (issue)
[21396](https://github.com/huggingface/transformers/issues/21396)

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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      Pull Request section?
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- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

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@ArthurZucker and @younesbelkada

_The documentation is not available anymore as the PR was closed or merged._<|||||>Yes, just pass along `device_map="auto"` or `device_map="balanced"` in your call to `from_pretrained` to have the model be parallelized. It will work for training and inference.<|||||>Oh sweet! Didn't know about this.  I just tried training with the longt5 3b model using accelerate and it didn't work well; GPU0 got most of the workload and the training run crashed quickly.  I tried both "auto" and "balanced".  If I use my code it works.  I realize that I could specify my own device map, but that's pretty tedious. Is there a better way to debug this? Thanks!