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Classification models categorize input data into predefined labels. In this tutorial, we’ll build a food classification model to categorize food items using PromptRepo.
For classification, our dataset consists of:
Web page title The name of the web page
Web page content: Content of the page
Nutrition category: The correct category label (e.g., Red Meat, Beverages, Cheese, etc.)
Open Google Sheets and add or import the training dataset
Click Extensions > Promptrepo > Train AI
Promptrepo sidebar widget will be displayed
Enter the AI model name and click Next
Select Web page title & Web page content as input columns and click Next
Select Nutrition category as the output column, select Enum for the Treat as option and click Next
Note: In the output column, choosing Enum for the Treat as option for nutrition category makes it a classification model
Click Publish and let Promptrepo fine tune the classification model
Once trained, test the model by inputting a food name and its description
The model should predict the correct category
Classification models are foundational for structuring data. Now, let’s explore how to build an extraction model for retrieving structured data from unstructured text.
Click Submit to finish.
