A toolkit that streamlines and automates the generation of model cards

A vendor-neutral, pattern-first AI strategy playbook by Textstone Labs. Practical frameworks, governance models, evaluation tools, and ready-to-use templates to go from business problem → deployment → adoption.

LinkML rendering of model cards

Small program to scrape model repository data from the Hugging Face Hub

Data Cards for Time Series

GitHub-native ML System Cards: evidence-backed, PR-first documentation for ML systems

Model validation for GitHub pull requests — regression detection, data quality checks, and model cards in one Action. No server required.

How to document an AI/Machine Learning Model

AI governance for healthcare ML. Bias detection, fairness metrics, FDA-ready model cards, responsible AI.

🤖 Production-ready Python registry for OpenAI models with parameter validation, pricing data, and CLI tools. Supports GPT-5, Azure OpenAI, automated updates, and enterprise deployment.

AIWG training-complete framework — corpus-to-dataset pipeline with SKILL.md agentic surface and optional Python runtime backend. Marketplace plugin for AIWG.

Dataset of Model Cards for Language Models.

Curated AI model cards, comparison guides, pricing tables, and practical resources for choosing the right AI model

Automated AI model card generation from training metadata. Produces NIST RMF, EU AI Act, and HuggingFace-compatible cards in YAML/JSON/Markdown.

A model card for the CheXNet model.

AI governance + analyst-in-the-loop oversight demo using open-source geo/text data