Model Card

A required piece of model documentation that describes an AI model's purpose, intended use, training data characteristics, performance metrics, limitations, risk mitigations, and versioning; providers must maintain and provide model cards on request to support transparency, procurement checks, and conformity assessments.

A standardized document that describes an AI model's intended purpose, training data characteristics, performance metrics, known limitations, fairness considerations, and recommended deployment constraints to support transparency, explainability, and accountable use.

A standardized form of documentation that summarizes an AI model's purpose, training data, performance metrics, limitations, and appropriate use cases to improve transparency and enable meaningful explanations for users and auditors. The Approach Document endorses model cards as part of documentation standards for responsible procurement, deployment, and audit readiness.

A concise, standardized document describing a model's intended use, performance across relevant metrics, known limitations, evaluation results, and provenance information. Model cards are required by the Guideline to support transparency, informed deployment and monitoring.

A standardized form of technical documentation that summarizes a model's provenance, architecture, training data characteristics, evaluation metrics, intended uses, known limitations, and mitigation measures; required for transparency, audits, and conformity assessments of high‑risk systems.

A standard artefact recommended by the Playbook that documents a model's intended use, training data provenance, performance metrics, known limitations, risk mitigations and operational controls to support transparency, procurement assurance and auditability.

A standardized artifact describing an AI model's intended use-cases, training data provenance, performance metrics, known limitations, fairness evaluations, and maintenance needs to support transparency, procurement, and auditing.

A standardized documentation artifact that summarizes a model's intended purpose, characteristics of training and evaluation data, performance metrics, limitations, and known risks to support transparency, procurement, and auditing of AI models.