RAG README & pl version updated
# What does this PR do?

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The current code for fine tuning examples/research_projects/rag' can't be executed without passing `--distributed_retriever ray` parameter.

In addition, `pytorch-lightning==1.5.10`  should be recommended to prevent other miscellaneous error.

## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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      Pull Request section?
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- [ ] Did you write any new necessary tests?


## Who can review?
@patrickvonplaten @shamanez 

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
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

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The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20466). All of your documentation changes will be reflected on that endpoint.<|||||>> Thanks for your PR, but we don't maintain this example, nor do we want to update it to more recent versions of any libraries it uses

Hi, thanks for the reply. This PR is late response for https://github.com/huggingface/transformers/issues/18704#issue-1345102153 issue. Nevertheless, if this PR can't be accepted now, can you tell me the reasons for not mainitaining RAG?<|||||>The RAG model is maintained, it's just this example which is not. It clearly says in the README it should be run with PyTorch ligthning 1.3.1. If you want to run it with a more recent version you need to adapt the script, probably as you did, but I'm not changing what the original authors have done in this research project.

Maintained examples are in the pytorch/tensorflow/flax subfolders of the examples folder.<|||||>Agree with @sgugger actually (sorry for approving it)

But, ok for me to also update the example since fine-tuning RAG seems to be used quite a bit<|||||>@patrickvonplaten 

Actually, with the latest PL versions, we can't use **DDPPlugin**. So my suggestion is to move with ray_distributed_retriever only. If we update the code with the current changes, it will fail.

I've added a comment in this in my last PR.

https://github.com/huggingface/transformers/blob/main/examples/research_projects/rag/lightning_base.py#L269

So it would be better to come up with an if condition since ray_distributed_retriever's init function, doesn't take any parameters.

https://github.com/huggingface/transformers/blob/main/examples/research_projects/rag/distributed_ray_retriever.py#L87


@kaiiwoo <|||||>@shamanez Why not host an updated version of the example on your repo then link to it from here and our community page in the doc?<|||||>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.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.