ModelRefs / Model Hub — AI Glossary
Model Hub — AI Glossary
A centralized repository for storing, versioning, and sharing trained ML model artifacts.
Overview
Model hubs (HuggingFace Hub, MLflow Model Registry, W&B Artifacts, Vertex AI Model Registry) provide: model versioning, metadata (training config, metrics, data lineage), artifact storage, access control, and deployment integrations. Foundational infrastructure for reproducible ML and organizational model governance.
Reference details
| Topic | infrastructure |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
The generic category — a repository for sharing and versioning model artifacts — of which the Hugging Face Hub is the largest public instance. It differs from a model registry in audience and purpose: a hub distributes models to other people, a registry governs which internal version is promoted to production. Some products do both, which is why the terms get used interchangeably when they should not be.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Model Hub — AI Glossary.
Frequently asked questions
What is Model Hub?
A centralized repository for storing, versioning, and sharing trained ML model artifacts.
What concepts are related to Model Hub?
Closely related concepts include hugging face hub, model registry, experiment tracking.