- 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 card
- Navigate to the W&B Model Registry app.
- Select View details next to the name of the registered model you want to create a model card for.
- Go to the Model card section.

- Within the Description field, provide information about your machine learning model. Format text within a model card with Markdown markup language.
