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Document machine learning model

Add a description to the model card of your registered model to document aspects of your machine learning model. Some topics worth documenting include:

  • Summary: A summary of what the model is. The purpose of the model. The machine learning framework the model uses, and so forth.
  • Training data: Describe the training data used, processing done on the training data set, where is that data stored and so forth.
  • Architecture: Information about the model architecture, layers, and any specific design choices.
  • Deserialize the model: Provide information on how someone on your team can load the model into memory.
  • Task: The specific type of task or problem that the machine learning model is designed to perform. It's a categorization of the model's intended capability.
  • License: The legal terms and permissions associated with the use of the machine learning model. It helps model users understand the legal framework under which they can utilize the model.
  • References: Citations or references to relevant research papers, datasets, or external resources.
  • Deployment: Details on how and where the model is deployed and guidance on how the model is integrated into other enterprise systems, such as a workflow orchestration platforms.

Add a description to the model cardโ€‹

  1. Navigate to the W&B Model Registry app at
  2. Select View details next to the name of the registered model you want to create a model card for.
  3. Go to the Model card section.
  4. Within the Description field, provide information about your machine learning model. Format text within a model card with Markdown markup language.

For example, the following images shows the model card of a Credit-card Default Prediction registered model.

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