Enable BLIP for auto VQA
Author: regisss
Pull request: yes

# What does this PR do?

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When using a BLIP (not BLIP2) model with a pipeline for VQA, the following warning is displayed:
```
The model 'BlipForQuestionAnswering' is not supported for visual-question-answering. Supported models are ['Blip2ForConditionalGeneration', 'ViltForQuestionAnswering'].
```
Since there are some BLIP models for VQA on the hub (e.g. [this one](https://huggingface.co/Salesforce/blip-vqa-base)), this PR adds BLIP to the VQA auto class.


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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)

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Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_29499). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

Done @ArthurZucker! Actually it's just a warning so not sure the test would catch it.