docs:  New terms and updates to glossary
Updates to the glossary as proposed in #21801 .

All terms suggested in the issue were added, except for Encoder/Decoder. Acronyms were also added for terms in which it made sense (e.g. NLP)

Note that this PR replaces ***autoencoding models*** with ***encoder models*** (and provides a more detailed definition) as well as merging ***autoregressive models*** and ***causal language modeling*** with ***decoder models***.

This is my first draft and would likely benefit from additional edits/revision. Any suggestions in terms of updates or areas to expand further on are welcome 🙂 

# What does this PR do?

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Fixes #21801 


## Before submitting
- [x ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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      to it if that's the case.
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      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [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.

@stevhliu 

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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: @sgugger

Integrations:

- deepspeed: HF Trainer: @stas00, Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam

Documentation: @sgugger, @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)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: @sgugger
- TensorFlow: @Rocketknight1

 -->

_The documentation is not available anymore as the PR was closed or merged._<|||||>Thanks for the detailed edits, they are helpful! 🙂 I will refresh permissions and also add a link to the pipeline for inference doc tomorrow <|||||>Added my update, and I followed the instructions to refresh permissions. I don't seem to have permissions to manually restart the CircleCI Pipeline, so not sure whether the steps I took were reflected in my last commit (I did my updates before refreshing permissions). <|||||>You can push an empty commit with `git commit -m "Trigger CI" --allow-empty" and then push to your branch.<|||||>Thanks for the review! I'll start going over the changes / implementing your suggestions over the weekend <|||||>> Thanks for your PR. I don't think we should remove entries from the glossary. Linking to other entries is better. Could you also add an entry for "self-supervised learning" since most pretraining of Transformer models use that technique?

I will add back in the old entries and add links between them, and yeah that's a great idea!<|||||>Awesome! I committed the suggestion, looks to have merged successfully🙂 Thanks again for the help with the edits/reviews! (also feel free to ping me if you see any further edits/additions to be done)<|||||>The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_21982). All of your documentation changes will be reflected on that endpoint.