I am positively impressed by the number of responses you got! Looking at the “would you recommend” graph, most people seem to have taken questionnaire seriously, too. (Not too many trolls.)
Some things that I am surprised by:

I had expected more data scientists and ML engineers and less researchers
I am surprised that there are so many long-time users because it often feels that the library is continuously growing with many new users but less interaction from older users (perhaps the forums will change that!)
67, 9, 123 as a an answer to a “work or fun” question 


Big one: it seems that there is quite a preference for DataParallel over DistributedDataParallel. I wonder why this is. What are use cases where you can use DP but not DDP? In all other cases, DDP should perform better in terms of speed.
I do understand the comments about modularization, that the code base seems to be spread over too many files. On the one hand I think this can be partially solved by using a folder structure for the models, tokenizers, and utils. A directory structure already makes the code base more readable. On the other hand, though, since there is a lot of inheritance (e.g. PretrainedModel, BertModel, RobertaModel), you cannot get around separate building blocks. It is necessary to allow for custom models and rapid research where other building blocks can be reused.

The most important thing that I see in all of this, though, is the highlighted keyword in the likes: community. I definitely agree with it. The catch phrase of HF is to democratize NLP, and I strongly believe that this is exactly what you guys are doing. Let’s have the forum be another step into that direction. A big congrats on all the work that you do!