A Model Card built for AI governance.
Six guided steps produce a seven-section Markdown Model Card following Google's standard, with EU AI Act Article 11 + Annex IV field references inline so reviewers can trace what's covered.
Six steps · Seven sections · Reviewer-ready Markdown
Seven sections, Annex IV-traceable
- 01Model details
- 02Intended use
- 03Training data
- 04Evaluation + metrics
- 05Ethical considerations
- 06Limitations + recommendations
- 07Sign-off
Identify the model
Header fields that anchor the rest of the card. Annex IV §1 of the EU AI Act asks for a general description. This is it.
Whoever's accountable for the model in production.
Common questions
What the tool does, how it maps to AI Act technical documentation, and where its boundaries are.
What is a Model Card?
A Model Card is a short, structured document about an ML model: what it does, what it was trained on, how it performs, where it falls short, and how it should be used. The format was proposed by Mitchell et al. (2018) and has become a de-facto standard for ML governance documentation.
How does this relate to the EU AI Act?
Article 11 of the EU AI Act (Regulation (EU) 2024/1689) requires technical documentation for high-risk AI systems, with specific contents listed in Annex IV. A Model Card overlaps with Annex IV §1 (general description), §2 (training data + methodology), §3 (validation + testing), §4 (risks to fundamental rights), and §6 (post-market monitoring). The builder's output calls out each Annex IV section inline so reviewers can trace coverage.
Is this a replacement for the AI Act technical documentation file?
No. Annex IV requires a full technical documentation file covering 11 numbered topics: risk management system, data governance, human oversight, accuracy + robustness + cybersecurity, and more. The Model Card is one input to that file. Use this tool to generate the model-specific layer; pair it with the EU AI Act Risk Classifier and DPIA Generator for the regulatory + privacy layers.
Does the tool send my data anywhere?
No. Everything runs entirely in your browser: answers are kept in component state, the Markdown is generated locally, and nothing is transmitted, logged, or persisted server-side.
What does the export contain?
A seven-section Markdown document: Model details, Intended use, Training data, Evaluation + metrics, Ethical considerations, Limitations + recommendations, and Sign-off. Empty fields render as `_Not specified._` so structural gaps are visible to reviewers.
How does this connect to AIGP exam preparation?
The IAPP AIGP exam covers AI documentation practice: model cards, datasheets for datasets, and the EU AI Act's documentation requirements. Working through the builder mirrors the kind of practical reasoning the exam tests, and Startege's AIGP track maps documentation patterns to flashcards and practice scenarios.