Synthetic Data Generator
Use Language Models to Create Datasets for Specified Labels and Categories
Setup & Configure
Use Case
Labels
Use a colon to separate each label and its description as in 'label: description.'
Categories
Use a colon to separate each category and its subcategories as in 'category: type1, type2.'
Guiding Examples
Include all examples in this box. For each example, provide a LABEL, CATEGORY, TYPE, OUTPUT, and REASONING.
Generate & Export
Status
Actions
Enter the number of rows for the generated dataset, and optionally a Hugging Face repo ID.
Sample Output
I hope you're enjoying the slopes! If you need any assistance or have questions about our ski lessons, please don't hesitate to ask. We're here to help you make the most of your winter sports experience. | neutral | meta-llama/Meta-Llama-3.1-8B-Instruct | This text is polite because it expresses gratitude for the customer's trust and shows a willingness to help. The use of "We appreciate" and "We're happy to assist" convey a positive tone and a sense of customer care. Additionally, the phrase "Please let us know how we can provide a better experience for you today" demonstrates a commitment to customer satisfaction and a desire to improve their experience, which is a hallmark of polite |

This synthetic data generator, part of Intel's Polite Guard project, utilizes a specified language model to generate synthetic data for a given use case. If you find this project valuable, please consider giving it a ❤️ on Hugging Face and sharing it with your network. Visit
- Polite Guard GitHub repository for the source code that you can run through the command line on an AI PC or Intel Tiber AI Cloud,
- Synthetic Data Generation with Language Models: A Practical Guide to learn more about the implementation of this data generator, and
- Polite Guard Dataset for an example of a dataset generated using this data generator.
Privacy Notice
Please note that this data generator uses AI technology and you are interacting with a chat model. Prompts that are being used during the demo and your personal information will not be stored. For information regarding the handling of personal data collected refer to the Global Privacy Notice (https://www.intel.com/content/www/us/en/privacy/intelprivacy-notice.html), which encompass our privacy practices.