Improving pipeline tests
Author: Narsil
Pull request: yes

# What does this PR do?

This PR removes `small_models` in favor of random dynamic super small models from tiny_config.

- Main reason, so we can test the pipeline on as much architectures as possible (which is the goal of the pipeline)
- Main drawback, we don't test `fast` vs `non-fast` tokenizers anymore (non fast cannot be learned dynamically on the fly like
the fast tokenizers)
- We cannot test exact values either because the models are random. Introduces ANY help class to make output structure more readable within a test too !
- We don't test explicity TF vs PT outputs on the small tiny config (again random weights), but we will explicitely add those for the slow tests which are going to be much more explicit (with actual values being checked against)

Tl;dr small_models -> random weight with more configs out of the box, large_models, less but check more information within outputs.

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## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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## Who can review?

@LysandreJik 

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.

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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
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Comments:
So let's start to merge those iteratively ?

Yes :)