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Model Management

Use the W&B Model Registry as a central system of record for models.

  • Create Registered Models to organize your best model versions for a given task
  • Track a model moving into staging and production
  • See a history of all changes, including who moved a model to production

Model Registry Quickstart​

  1. Open your Model Registry and create a registered model.

  2. In your script, log a model as an artifact version.

    Open In Colab

    art = wandb.Artifact("my-object-detector", type="model")
    art.add_file("saved_model_weights.pt")
    wandb.log_artifact(art)

  3. From the Artifact page, link the artifact version to the registry.

Model Registry Features​

Model Versioning​

Iterate to get the best model version for a task, and catalog all the changes along the way.

  • Track every model version in a central repository
  • Browse and compare model versions
  • Capture training metrics and hyperparameters

Model Lineage​

Document and reproduce the complete pipeline of model training and evaluation.

  • Identify the exact dataset version the model trained on
  • Restore the training code, including git commit and diff patch
  • Get back to the model’s hyperparameters and other metadata for reproducibility
  • Dig in to upstream jobs that can affect model performance

Model Lifecycle​

Manage the process as a model moves from training through staging to production.

  • Highlight the best model versions that are being evaluated for production
  • Communicate where a model version is in the process — staging, production etc
  • Review the history of model versions that moved through each stage

Model Registry Pilot Limits​

This new feature is now turned on for all users to try for free, up to:

  • 5 Registered Models, with unlimited versions linked to each model
  • 10 most recent steps of Action History shown in the UI for each registered model

Explore more​

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