[WIP] Standardize inputs and outputs for existing image-text-to-text models
Author: yonigozlan
Pull request: yes

# What does this PR do?

Pull request aimed at laying the groundwork for adding the image-text-to-text pipeline, while waiting for #31911 to be resolved, by standardizing inputs and outputs for existing image-text-to-text models in Transformers. Follows #29572.

Models whose processors need to be checked/modified:

- [x]  GIT
- [x]  BLIP
- [x]  BLIP-2
- [x]  IDEFICS
- [x]  InstructBLIP
- [x]  LLaVa
- [x]  Fuyu
- [x]  Pix2Struct/DePlot/MatCha
- [x]  UDOP
- [x]  Donut
- [x]  KOSMOS-2
- [ ]  Idefics2
- [x]  LLaVA-NeXT
- [x]  PaliGemma
- [x]  VipLlava

If I forgot or misidentified any models, please feel free to add or remove them!

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## 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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      [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?

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.

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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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@zucchini-nlp @amyeroberts @NielsRogge 

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32059). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.