Fix Llama QnA `from_pretrained`
Author: vasqu
Pull request: yes

# What does this PR do?
Fixes issues with llama for qna when using `from_pretrained` to load any base model. Currently, when we load any llama model, we get a 100% mismatch (i.e. everything is randomly initialized). The workaround is to manually save the (base) model and then load it from disk (ref. #30381):
```python
from transformers import AutoModel, AutoModelForQuestionAnswering
model = AutoModel.from_pretrained("meta-llama/llama-2-7b-hf")
model.save_pretrained("base_model")
model = AutoModelForQuestionAnswering.from_pretrained("base_model")
```
This is very unintuitive and goes against the usage of auto classes and from_pretrained which should be quick and easy. 

I tried to use loading hooks in #34038 to keep it BC but to no avail (I could fool the error messages tho :D). So it might be breaking older versions which I think is warranted to ensure having an easy `from_pretrained` call instead. #29258 tried the same at first to and then opted for a version which doesn't work as expected.

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Comments:
I have seen issues with from from_pretrained, long due a fix for them 👀 

Yes, it would be completely breaking :/ I've tried using some loading hooks which didn't work but I don't have the time to properly look into this atm. 

Should I close this then? 

@ArthurZucker Any updates on this? Should I close this? :eyes: 

Hey sorry no, It's on my TODO list, hope to get to it next week! 

No worries!

BTW I think we can close this, #36033 should make it easier to update without breaking

Nice, will close then 👍