task_categories:text-generation size_categories:n<1K language:en license:openrail art region:us
---
dataset_info:
  features:
  - name: name
    dtype: string
  - name: review
    dtype: string
  - name: average_review
    dtype: string
  - name: menu
    dtype: string
  - name: stars
    dtype: string
  splits:
  - name: train
    num_bytes: 61707
    num_examples: 13
  dataset_name: json

license: openrail
task_categories:
- text-generation
language:
- en
tags:
- art
pretty_name: Product Descriptions and Ads
size_categories:
- n<1K
---
# Synthetic Dataset for Product Descriptions and Ads

The basic process was as follows:

1. Prompt GPT-4 to create a list of 100 sample clothing items and descriptions for those items.
2. Split the output into desired format `{"product" : "<PRODUCT NAME>", "description" : "<DESCRIPTION>"}
3. Prompt GPT-4 to create adverts for each of the 100 samples based on their name and description.

This data was not cleaned or verified manually.