Easier Model Serving with zerocopy

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Easier Model Serving with zerocopy 

Fri August 19, 2022 04:07 PM

A comparison of the code to deploy our example intent detection model, before and after applying zero-copy model loading to the deployment. Only two lines of code need to change. See below for a detailed description of the changes.

In a
previous post, we introduced the concept of zero-copy model loading. Zero-copy model loading involves keeping the weights of a machine learning model in shared memory so that different processes can load the model for inference instantly without copying data.
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