modelinventory
Model inventory is a centralized catalog that stores information about machine learning models, their versions, artifacts, and related metadata. It supports discovery, reuse, deployment, and governance by providing a single source of truth for models across an organization. A well-maintained model inventory helps teams track provenance, compare alternatives, and ensure reproducibility.
Key components typically included are model metadata (name, version, authors, license), lineage (data sources, training code,
Lifecycle and governance aspects focus on registration, validation, promotion through stages (e.g., development, staging, production), monitoring,
Common tools and platforms provide model registries and inventory capabilities, including MLflow, Kubeflow, DVC, Weights & Biases,
Benefits of a model inventory include improved traceability, faster model reuse, standardized governance, and better risk