Standardize image-text-to-text-models outputs
Author: yonigozlan
Pull request: yes

# What does this PR do?

Standardize outputs for existing image-text-to-text models by adding a `post_process_image_text_to_text `function to their processor.
Blocking PR for `image-text-to-text` pipeline.

The following models' processors need to be 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
- [x]  Idefics2
- [x]  LLaVA-NeXT
- [x]  PaliGemma
- [x]  VipLlava
- [x] Chameleon
- [x] LlaVa OneVision
- [x] Qwen2-VL
- [x] Idefics3
- [x] Pixtral
- [x] MLlama

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## Who can review?

@molbap @amyeroberts 

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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:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32471). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

@yonigozlan Chameleon can also do image-text-to-text

> @yonigozlan Chameleon can also do image-text-to-text

Thanks! Will add it to the list

@LysandreJik This should be ready for a final review, and should significantly reduce the loc count and number of files changed for the [image-text-to-text pipeline](https://github.com/huggingface/transformers/pull/34170) PR :).
One thing to note is the use of a "legacy" kwarg for BC, as some changes are needed in the preprocessing of some models if we want them to work seamlessly with the image-text-to-text pipeline. I'm open to suggestion if there is a better way to handle this

cc @molbap can you do an initial review please?

Maybe not initial, but pre-final ? :grin: 

The changes from this PR were merged in https://github.com/huggingface/transformers/pull/34170