[Flax] Correctly Add MT5
Author: patrickvonplaten
Pull request: yes

# What does this PR do?

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During the Flax sprint many teams weren't aware that mt5 models can be used with the `FlaxT5ForConditionalGeneration` class. This is mainly because the docs currently state that FlaxMT5 is not implemented: https://huggingface.co/transformers/index.html#supported-frameworks and because there are no docs on FlaxMT5, but for PyTorch & TF (https://huggingface.co/transformers/model_doc/mt5.html).

This PR adds a FlaxMT5 class analog to PT and TF and also adds official Flax weights to `mt5-base`, etc.: https://huggingface.co/google/mt5-base/commit/0b908f9e3c2fabccc4ab411b89838cecdd9ad499

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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:
> Do we really need to add an extra class? Can't we just have the auto-mapping point to a FlaxT5Model?

Technically we don't need it, my main arguments are:

- Consistency with PyTorch & TF (people thought MT5 can't be used with Flax because https://huggingface.co/transformers/model_doc/mt5.html doesn't have Flax classes)
- Ability to provide meaningful examples for MT5 in Flax. T5 is not multi-lingual so the examples might be misleading for Flax