TF Lite Model Metadata
Learn to add metadata to a TF Lite model using the TF Lite Metadata Writer API.
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Metadata refers to the data that describes other data or information. It provides additional information about data to help understand, manage, or use it more effectively. In the context of ML models, metadata can include information such as the model architecture, input and output shapes, preprocessing steps, training details, accuracy metrics, label files, and more. Let’s explore TF Lite metadata and the Metadata Writer API. We will also extract model information, input/output details, and associated files from a TF Lite model with metadata.
TF Lite model metadata
TF Lite model metadata is a self-descriptive format that contains information about the model, its inputs and outputs, and associated files. This information enables easy exchange and integration of models across different platforms and frameworks.
The primary uses of model metadata are:
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