Add CLIP resources
Author: eenzeenee
Pull request: yes

# What does this PR do?

Adds resources of CLIP according to [this issue](https://github.com/huggingface/transformers/issues/20055.)

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Part of #20055


## 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?

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.

<!-- 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: @muellerzr 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! Thanks for adding resources for CLIP. 
By the way, please fix `Part of #20555` to `Part of #20055` since 20055 is the issue of `Model resources contribution`.

Thank you for reviewing!! I fixed it!

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_26534). All of your documentation changes will be reflected on that endpoint.

> Thanks for fixing, can you also include the [training script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/contrastive-image-text) and [blog post](https://huggingface.co/blog/fine-tune-clip-rsicd) @NielsRogge linked to?

Sorry for the late reply. It seems to appear in 86 and 87 lines. Do you want me to change the description to something else?

> Do you want me to change the description to something else?

Should be good then! 👍