AI model card generator
A model card is the README for a machine learning model: a short, structured
document that states what the model does, what data trained it, how well it
performs, and — critically — where it should not be used. The AI model card
generator turns your inputs into a complete card in the Google and Hugging
Face standard layout, ready to drop into your repository as MODEL_CARD.md.
Everything is assembled locally in your browser.
How it works
You provide the building blocks — model name and version, task type, a summary of the training data, your evaluation metrics, intended and out-of-scope uses, known limitations, and ethical considerations. The generator slots each of these into the canonical model card sections (Model Details, Intended Use, Training Data, Evaluation, Metrics, Limitations, Ethical Considerations) and formats the result as clean Markdown. Sections you leave blank are filled with clear placeholder prompts so the card reminds whoever maintains it what still needs documenting, rather than silently omitting it.
Tips and notes
- Be explicit about out-of-scope use. The most valuable line in a model card is often “do not use this for X” — it prevents the most harmful misuse.
- Use real evaluation numbers. A card with vague performance claims is worse than none; quote the metric, the dataset, and the date.
- Name the limitations you know about. Bias in training data, weak languages, or brittle edge cases belong in the card, not in a postmortem.
- Version the card with the model. Update it on every retrain so the documentation never describes a model you no longer ship.