modeldescribe

ModelDescribe is a framework for generating concise, human-readable documentation of machine learning models and their behavior. It is designed to translate technical model specifications, training details, and performance metrics into descriptions that are accessible to stakeholders, auditors, and non-technical users.

The framework aims to cover the full lifecycle of a model, including its purpose, input and output schemas, training data sources, preprocessing steps, evaluation results, and known limitations. It emphasizes governance considerations such as versioning, provenance, bias and fairness notes, and deployment context to support accountability and regulatory compliance.

Core components typically include:

- Metadata extraction: collects model metadata, data lineage, and evaluation metrics.

- Descriptor generation: creates concise summaries of model architecture, training regime, and performance characteristics.

- Language rendering: uses templates or natural language generation to produce clear, neutral descriptions.

- Provenance and versioning: tracks changes across model revisions and deployments.

- Risk and governance notes: highlights potential biases, limitations, and compliance implications.

Workflow and usage often involve assembling model artifacts, running the metadata extractor, applying descriptor templates, rendering natural language descriptions, and publishing the resulting documentation to governance portals, model registries, or external reports. ModelDescribe supports transparency without exposing unnecessary technical detail, making it useful for audits, stakeholder communication, and onboarding.

Benefits include improved documentation consistency, easier audits, and enhanced communication of model intent and risks. Limitations include the potential for oversimplification or outdated descriptions if updates are not maintained, and the need for careful language curation to avoid misinterpretation.

See also: model documentation, model governance, explainable AI, model auditing.