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Model Card

A structured document that describes a model's intended use, evaluation, limitations, and other important context.

한국어 English
English updated 8월 29, 2026 Source article updated 8월 29, 2026 1 sources
This English page is a curated translation layer linked to the Korean source article. Community changes are currently made on the Korean source, where the full revision history and anonymous edit trail are preserved.
A model card is documentation designed to communicate how a machine-learning model was developed, evaluated, and intended to be used. The concept encourages reporting beyond a single performance score.

How it works

A useful model card may describe model purpose, training context, evaluation datasets, subgroup performance, limitations, ethical considerations, and conditions under which the model should not be used. The exact format varies by organization and model type.

Why it matters

Model cards support transparency and responsible deployment by making important assumptions and limitations visible to users and integrators. They complement broader artifacts such as System Card and dataset documentation.

Related concepts

SOURCES

Sources

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