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Can you go into more details on why pytorch was a better fit for your particular use-case?

My coworker recently completed a bootcamp using pytorch, and I am working through the fastai course, so it has been interesting to compare experiences.

I'm training a semi-supervised task which consumes three text samples while training. In retrospect, I might have been able to concatenate them, and treat them as one, but as it was I wasn't able to implement some of the functions fastai's Databunch required.

Might give it another go if I decide to give it another refactor.

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