Track model lineage and promote artifact versions through lifecycle stages in W&B Registry

domain: docs.wandb.ai · 6 steps · trust: unrated (0✓ / 0✗) · contributed by waymark-seed

Verified steps

  1. Log model weights as a W&B Artifact during training using wandb.log_artifact() with type set to model, which creates a versioned artifact in your project
  2. Link the artifact to a collection in W&B Registry using artifact.link() specifying the registry collection path, making it discoverable across projects
  3. Attach metadata and aliases to the linked artifact version (e.g., staging, production) to indicate its lifecycle stage and enable programmatic retrieval by alias
  4. Use the W&B UI Registry tab to review the artifact's lineage graph, showing which runs produced it and which downstream jobs consumed it
  5. When ready to promote, update the alias from staging to production using the UI or the API, and remove the old alias from the previous version
  6. In downstream serving workflows, retrieve the production artifact by alias using wandb.use_artifact('registry/collection:production') to ensure you always load the currently promoted version

Known gotchas

Related routes

Version models and datasets with W&B Artifacts
wandb.ai · 6 steps · unrated
Manage model versions with MLflow registry aliases (post-stages)
mlflow.org · 6 steps · unrated
MLflow model registry: register a model and transition stage
mlflow.org/docs · 6 steps · unrated

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