Changed the hidden_size to d_model for XLNET docs
# What does this PR do?
Changes the use of hidden_size to d_model as XLNET model (unlike BERT and other) uses `d_model` instead of `hidden_size`.

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Fixes #11938 


## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).


## Who can review?
@sgugger @NielsRogge 

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Many models use different names for this and `hidden_size` is a constant property that works for all of them, so we will keep the docstrings updated with this. It also simplifies copy-pasting the docstrings between models.<|||||>> Many models use different names for this and `hidden_size` is a constant property that works for all of them, so we will keep the docstrings updated with this. It also simplifies copy-pasting the docstrings between models.

Okay, in that case at least we can mention somewhere in the documentation of the XLNET that hidden_size is same as d_model. Because for someone who starts working with XLNET and has not worked with other models won't understand what is hidden_size, as hidden_size is not described in XLNET docs and is mentioned as one of the dimensions in the output. <|||||>How about adding an entry in the glossary page, along with input IDs, attention mask etc?<|||||>> How about adding an entry in the glossary page, along with input IDs, attention mask etc?

along with.. means inside those sections [input IDs section, attention mask section] or creating another section for it?

If thinking of adding it to the glossary we can write a line in docs of XLNET, BERT ..(other models) that explanation of some terms can be explored in the glossary. As all the documentations (pandas, pytorch... etc) don't have a glossary section and it can't be expected from the reader that he/she will search for glossary section if they encounter any term not explain in a documentation page.

<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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