An evaluation harness is a structured framework for systematically testing and measuring AI model performance using predefined benchmarks. It standardizes input formatting, runs evaluations consistently, and aggregates results. Developers use it to validate model accuracy, identify weaknesses, and compare versions. Data scientists, ML engineers, and researchers benefit by ensuring reliable, reproducible assessments before deployment.
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