fraud is a python package designed to streamline synthetic data for finetuning machine learning models.
Data scarcity is a limiting factor. While real data is the ideal solution; however it is often expensive, time-consuming, and resource-intensive.
Synthetic data offers an effective middle ground, enabling models to significantly enhance their performance by supplementing smaller datasets.
Here's a basic example to get you started.
import fraud as fr
synthetic_samples = fr.from_str('Could you please meet {name} at {time}', 20)Grab a sample from your dataset to make a template from it!
import fraud as fr
predicted_template = fr.predict_template(
sample='My name is Trevor and I am a Data Scientist.',
labels=['name','job'],
threshold=0.5
)
fr.from_str(predicted_template, 5)