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We are trying to give a model to collaborators but would like to protect the IP. What are some ways to encrypt/hide/compile the definition when sharing a trained model?

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One way to protect the IP of a trained model is to put the model behind an API. Give only limited API end-point access.

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  • $\begingroup$ Yes, something like docker. I did think of that one. Is there no way to "compile" a model to something like a binary? $\endgroup$
    – illan
    Feb 8 at 22:18

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