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On February 10th, John transferred $500 from his account in New York to an offshore account in Hong Kong, on the same day he transferred $250 to a bank in Zurich.
0suspicious
A transaction of $500 was made at a local store in New York on March 22, 2023. A person who works at this store often makes purchases of $200 and $300 on a regular basis.
1legitimate
On February 10, 2023, a customer in New York made a transaction of $500 at a local store using their debit card. The transaction occurred on the same day at the same store.
1legitimate
A customer in New York made a purchase of $1,500 on February 22nd at a retail store, using their debit card, and the transaction was flagged for review.
1legitimate
A customer from New York made a payment to a company called 'Tech Services Inc. via credit card on the 10th of this month, the payment amount was $520
1legitimate
Customer from California made a 7,300 dollar purchase in a single transaction from a remote location in China.
0suspicious
Transaction from Alice Smith, date: 2022-07-25, amount: $450.00, location: New York
1legitimate

Built with Distilabel

Dataset Card for my-distiset-8c8b91dc

This dataset has been created with distilabel.

Dataset Summary

This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:

distilabel pipeline run --config "https://huggingface.co/datasets/daefeaf/my-distiset-8c8b91dc/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/daefeaf/my-distiset-8c8b91dc/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default
{
    "label": 0,
    "text": "On February 10th, John transferred $500 from his account in New York to an offshore account in Hong Kong, on the same day he transferred $250 to a bank in Zurich."
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("daefeaf/my-distiset-8c8b91dc", "default")

Or simply as it follows, since there's only one configuration and is named default:

from datasets import load_dataset

ds = load_dataset("daefeaf/my-distiset-8c8b91dc")
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