Added FAN Models
Author: kiansierra
Pull request: yes

# What does this PR do?

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Fixes #17234

Implements the FAN Models described in this [paper](https://arxiv.org/pdf/2204.12451.pdf) and available in the following [github repo](https://github.com/NVlabs/FAN), Additionally this repo has some of the weights available as described in their README file.


## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [X] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [X] 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).
- [X] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

@NielsRogge

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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->


## Tasks Completed

From those provided in the [add new model](https://huggingface.co/docs/transformers/add_new_model) contribute section

- [X] (Optional) Understood the model’s theoretical aspects
- [X] Prepared 🤗 Transformers dev environment
- [X] Set up debugging environment of the original repository
- [X] Created script that successfully runs the forward() pass using the original repository and checkpoint (Available in Demo Colab)
- [X] Successfully added the model skeleton to 🤗 Transformers
- [X] Successfully converted original checkpoint to 🤗 Transformers checkpoint
- [X] Successfully ran forward() pass in 🤗 Transformers that gives identical output to original checkpoint
- [X] Finished model tests in 🤗 Transformers
- [X] Successfully added tokenizer in 🤗 Transformers
- [X] Run end-to-end integration tests
- [X] Finished docs
- [X] Uploaded model weights to the Hub
- [X] Submitted the pull request
- [X] (Optional) Added a demo notebook  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/10aCWtEPpRD2X251EiCNemjhvxmsQhGCl)


## Model files migration

Ideally I believe the different model files for these architectures should be hosted under the [NVIDIA](https://huggingface.co/nvidia) organization, instead of my own [personal space](https://huggingface.co/ksmcg).

## Thank you note

It has been a very enriching experience to migrate these models. I've learned a lot while developing under the constraints imposed by this library that provide such a great consistent user experience, from the tests, PreTrainedModel class, the cookiecuter template.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20288). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20288). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20288). All of your documentation changes will be reflected on that endpoint.

Hi @NielsRogge , thanks for your review.
I believe the current tests that are failing are not due to this PR (mostly because the failure makes reference to a file not modified by this PR) (torch tests passed in a previous run).
Please let me know if there any additional tasks to complete