Model Card

A Model Card is a standardized document that describes a machine learning model's purpose, training data, intended uses, limitations, evaluation results, and known risks. The concept was introduced in a 2018 paper by Mitchell, Raji, Gebru, and colleagues at Google. A well-written model card answers: what does this model do? Who built it? What data was it trained on? Where does it work well? Where does it fail? Who should not use it? Famous examples include the model cards published for OpenAI's GPT-4, Meta's Llama family, Google's Gemini, and most models on Hugging Face Hub. The EU AI Act's GPAI documentation requirements draw heavily on the model-card pattern, and the NIST AI Risk Management Framework references it as a key transparency artifact. Mature enterprise AI programs require model cards for every deployed AI system — internal or vendor-provided — as foundational AI governance, AI compliance, and responsible AI documentation supporting AI risk management throughout the lifecycle.

Centralpoint Stores and Surfaces Model Cards in One Place: Oxcyon's Centralpoint AI Governance Platform inventories every AI system alongside its model card, no matter the underlying model (OpenAI, Gemini, Llama, embedded). Centralpoint meters consumption, keeps prompts and skills on-prem, and embeds card-aware chatbots into your portals via a single JavaScript line.


Related Keywords:
Model Card,,