I couldn’t find a super simple explanation of ML model cards that didn’t drag in a lot of extra information, so I had ChatGPT generate one and am liberating here to help inform other people searching on the topic:
ML Model Cards are a way to document and communicate important information about a machine learning (ML) model.
Think of them like nutrition labels on food products. Just as nutrition labels provide information about the ingredients and nutritional content of a food product, ML model cards provide information about the dataset used to train the model, the model architecture, the performance of the model, and any limitations or potential biases that may exist.
ML model cards can help users understand the strengths and weaknesses of a model, as well as any potential risks or limitations associated with its use. This information can be particularly important when making decisions about whether to use a particular model in a real-world application, and can help ensure that the model is used in a responsible and ethical way.