Generative models generate new outputs based on learned patterns. In this tutorial, we’ll create a model that generates nutritional estimates for food items when real data is unavailable.

Step 1: Preparing Training Data

For generation, our dataset consists of:

Web page title: The name of the Web page.
Web page content: The content of the web page.
Nutritional category: Category of the nutrition such as beverages, general food etc.,.
Ingredients: Source ingredients of the food product.
Nutrition per serving: Nutritional values per serving of the food item.
Serving size (grams or mL): size of one serving of the food item
Nutrition information available in the input: the nutritional values of the food available in the input
Guessed nutrition: the nutritional information of the food that weren't given and was predicted instead

Step 2: Uploading Data to Promptrepo

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
Choose all other columns as output columns and click Next

Step 3: Training & Testing the Model

Click Publish and let Promptrepo fine tune the generative model
Once trained, test the model by inputting a food name and its description
The model should extract structured data (ingredients & nutrition) from the input text. If real data is missing, the model will generate a reasonable estimate based on similar foods.

Generative models are powerful for filling gaps where real data is unavailable. With Promptrepo, you can fine-tune AI models for classification, extraction, and generation with ease. Whether you are structuring unorganized data, extracting key details, or generating insights, Promptrepo makes AI training accessible and efficient.

Promptrepo

Formfacade

Formesign

Neartail

How to Build a Generative Model with Promptrepo?

Step 1: Preparing Training Data

Step 2: Uploading Data to Promptrepo

Step 3: Training & Testing the Model

Finetune AI using data in Google Sheets