Optimizing ML Model Loading Time Using LRU Cache in FastAPI 📈

Published: 08 May 2023
on channel: Andrej Baranovskij

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Are you facing challenges with the time it takes to load large ML models in your backend API? This video presents a practical solution: utilizing LRU cache with properly annotated functions. Implementing this approach will make your model cached in memory, eliminating the need for disk reads on subsequent calls. Enhance the efficiency and performance of your ML workflow by incorporating LRU cache techniques. Join us to learn more about this valuable strategy! 📘🖥️

Sparrow - data extraction from documents with ML:
https://github.com/katanaml/sparrow

0:00 Introduction
0:48 Sparrow
1:38 Code
2:33 LRU Cache
5:55 Summary

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#python #fastapi #machinelearning

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