PhiMoE
Author: garg-amit
Pull request: yes

# What does this PR do?

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Integrates `PhiMoE` into transformers. https://huggingface.co/microsoft/Phi-3.5-MoE-instruct


## Before submitting
- [ ] 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#create-a-pull-request),
      Pull Request section?
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      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.

@ArthurZucker @gante 
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Models:

- text models: @ArthurZucker
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

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Comments:
@ArthurZucker @gante can I please get a review?

Hi, it seems to be a very important and awaited PR!:) Other frameworks are willing to integrate MoE too, like in litgpt [https://github.com/Lightning-AI/litgpt/issues/1686](https://github.com/Lightning-AI/litgpt/issues/1686). 

We are very much willing to integrate it as well 🤗 just came back from the torch conf, was a bit OO because of it 😢 

TLDR, overall the mixer needs to be properly documented and written to be more understandable! 

@ArthurZucker Thanks for reviewing the PR. I’ve refactored the code according to your suggestions, and it’s ready for another look. Also, the failing test case appears to be unrelated to this PR. Please let me know if it needs to be addressed.

Reviewing! 🤗 

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_33363). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

@ArthurZucker Thanks for reviewing! I've addressed the comments and moved `PhimoeRotaryEmbedding` out of the `PhimoeAttention` class.

Thanks everyone and @garg-amit for bearing with me! Congrats on the model release again 🤗