[r/LocalLLaMA] I replaced thousands of LLM classification calls with a ~230KB local model

Summary

A developer successfully replaced thousands of external LLM classification calls with a tiny, local ~230KB model. This approach addresses common issues like per-token costs, data privacy concerns, and model drift associated with using large language models for repetitive tasks such as categorizing contract clauses or support tickets. The solution involves training a small model on just ~50 labeled examples from the dataset, offering a highly efficient and secure alternative.

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