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Jax is a competing computational framework that does something similar to PyTorch, so both of your questions don't really make sense.

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Maybe deisteve will answer for himself, but I don't think that's meant to mean how to run Jax on Pytorch, but rather the questions he's interested in for any published model.

if a paper releases code in PyTorch im not going to sit there and complain Jax is more efficient

its like fretting about how everything should be written in C++ instead of Python/Javascript

I don't care.

can i run pytorch code on jax?

if not im not interested. i'll keep using pytorch.

i hope this answer makes more sense for you.

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