Add LLaMA resources
Author: eenzeenee
Pull request: yes

# What does this PR do?
Adds resources of LLaMA according to [this issue](https://github.com/huggingface/transformers/issues/20055.)
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Part of #20555


## 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).
- [ ] Did you write any new necessary tests?


## Who can review?

@stevhliu, @jungnerd, @wonhyeongseo may you please review this PR?

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerz and @pacman100

Integrations:

- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc and @younesbelkada

Documentation: @stevhliu and @MKhalusova

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:
LGTM! Please change this PR to `Open`.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_25859). All of your documentation changes will be reflected on that endpoint.

Awesome job, @eenzeenee! 👏 

For your final OSSCA report, consider these points:
- 💡 Share your insights on potential enhancements for the resource.
- 🚀 Reflect on the major challenge faced during this PR and your strategies to overcome it.
- 🌱 Tell us about your upcoming adventures in the world of open source!

Keep up the fantastic work! 🎉

One question, @stevhliu 
Since Alpaca's backbone is LLaMA, can we add the resources of Alpaca in this doc? 

> Since Alpaca's backbone is LLaMA, can we add the resources of Alpaca in this doc?

I think there are also several other variants of fine-tuned LLaMAs besides Alpaca, so for now, it may be better to just keep the focus on LLaMA.

Hello @stevhliu, may you please review this PR? Thank you! 😊