Model Card

A model card is a structured documentation artifact for an AI model covering its intended uses, training data, evaluation results, limitations, and ethical considerations, proposed by Mitchell et al. in a 2018 Google paper. Model cards have become standard practice for LLM releases: Hugging Face requires model cards for hosted models, every major frontier lab publishes model cards alongside model releases (Llama, Gemma, Mistral, Qwen, Phi), and the EU AI Act requires documentation analogous to model cards for high-risk AI systems. A model card typically includes sections for model details, intended use, factors (demographic, environmental, instrumentation), metrics, evaluation data, training data, quantitative analyses, ethical considerations, caveats, and recommendations. Tools like Hugging Face's modelcard library, Google's Model Card Toolkit, and various enterprise documentation platforms support model card generation. AI governance teams use model cards as the primary documentation interface between model providers and downstream users, and as evidence in regulatory submissions and compliance audits. Model cards are required reading before any model deployment decision.

Model-card-documented governance through Centralpoint: Centralpoint maintains an inventory of model cards across whichever LLMs your stack uses, supporting AI compliance documentation and audit-readiness. Tokens are metered per skill, prompts stay local, supports generative and embedded models, and deploys documented chatbots through one line of JavaScript on any portal.


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