[`Docs` / `BetterTransformer` ] Added more details about flash attention + SDPA
# What does this PR do?

as discussed offline with @LysandreJik 

This PR clarifies to users how it is possible to use Flash Attention as a backend for most used models in transformers. As we have a seen some questions from users asking whether it is possible to integrate flash attention into HF models, whereas you can already benefit from it when using `model.to_bettertransformer()`, leveraging the `BetterTransformer` API from 🤗  optimum. 

The informations are based from the [official documentation of `torch.nn.functional.scaled_dot_product`](https://pytorch.org/docs/master/generated/torch.nn.functional.scaled_dot_product_attention.html?highlight=scaled_dot_product_attention#torch.nn.functional.scaled_dot_product_attention)

In the near future, we could also have a small blogpost explaining this as well

To do list / To clarify list:

- Clarify that it is possible to do that for training as well (I did not added much on the training section)
- Maybe add a few lines in overview of performance and scalability to emphasize this?

Let me know if I missed anything else

cc @fxmarty @MKhalusova @stevhliu 
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_25265). All of your documentation changes will be reflected on that endpoint.<|||||>Thanks a lot for the extensive review @stevhliu ! 🎉 