1. Because they're researchers, not devops experts. They release the model in the way that they are most familiar with, because it's easiest for them. And I say that as someone who's released/open-sourced a lot of AI models: I can see how Docker is useful and all that, but why would I invest the time to do package up my code? It took long enough to cut through the red tape (e.g. my company's release process), clean up the code, document stuff. I did that mostly because I had to (red tape) or because it also benefits me (refactorings & docs). But docker is something that is not immediately useful for myself. If people find my stuff useful, let them do it and repackage it.

2. most people using these model don't use them in docker files. Sure, end users might do that. But that's not the primary target for the research labs pushing these models out. They want to reach other researchers. And researchers want to use these models in their own research: They take them and plug them into python scripts and hack away: to label data, to finetune, to investigate. And all of those tasks are much harder if the model is hidden away in a container.