summarization

While running the tutorials is not rare to meet with UserWarnings that are caused by underlying dependencies like transformers or pytorch. I think UserWarnings that are triggered by Haystack's or the user's code should stay visible, but those coming from dependencies could be hidden, as there's nothing we or the final users can do about it.

Examples:

• Tutorial 1: `/home/sara/work/hayst

We need to move the execution of CLI scripts used to build the documentation into a Make file. Wise suggestion from @louisguitton: DerwenAI/pytextrank#159 (comment)

Need help for retraining and cross validation and see if the ROUGE score matches exactly (or better) with the numbers reported in the paper.
I just train for 500k iteration (with batch size 8) with pointer generation enabled + coverage loss disabled and next 100k iteration (with batch size 8) with pointer generation enabled + coverage loss enabled.

It would be great if someone can help re-r

A next step for better generation is to implement a beam search for the generation. An example of it can be seen on the huggingface repo here, and this would need adding such a function to the GenerativeT5 model in onnxt5/models.py