summarization

Many users in our community have been asking to have easier ways to return the output of intermediate nodes. I can see that this could be very useful for debugging and also qualitative evaluation.

I think this feature would be very useful, though the exact design is not yet fully clear.

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