HF models integration of MONAI networks

[surajpaib]

Is your feature request related to a problem? Please describe.
#7833 Continuing the thread here.

HF has grown largely as a model hosting platform. Offering MONAI networks pretrained weights on HF would be very useful in sharing models with the larger community. I'm envisioning this way to be more a developer friendly way to load models for inference and fine-tuning in their own pipelines - outside the bundle ecosystem.

Describe the solution you'd like
#7833 suggests a nice solution, however, further discussion was pending on the implementation specifics.

The Hub suffix for each model was the proposed option by @ericspod.
Another way to offer this functionality could be through dynamic class creation using type so the user can just call a wrapper function and add HF capabilities to MONAI models.

Describe alternatives you've considered
Creating an independent package with class composition for offering specific models https://github.com/project-lighter/lighter-zoo/blob/master/lighter_zoo/wrappers.py

[ericspod]

We should definitely come back to HF integration. There is also this related tutorial: Project-MONAI/tutorials#1946

[surajpaib]

@ericspod Perfect. This should make the model loading part in the pipeline much more straightforward and offloaded to HF.

Happy to help as needed - this would be of great help to our project!

[ericspod]

Hi @surajpaib we've done some work for HF integration in #8403. I think this and the work on the model zoon to integrate with HF here goes a way towards addressing the requirement here. We've focussed on bundles being on HF, does that help address your requirements here?

[surajpaib]

Thanks for the update @ericspod

As you pointed out, this is focused on bundles on HF.

My use-case is for a MONAI network with pre-trained weights, rather than a bundle, to have the ability to pull from HF. This could be useful for other codebases using MONAI networks to ship weights in a more unified way.