Metadata-Version: 2.2
Name: fraud
Version: 0.1.2
Summary: Simple Synthetic Data with Python
Project-URL: Homepage, https://github.com/TrevorW-code/fraud
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.12
Description-Content-Type: text/markdown
Requires-Dist: faker==33.1.0
Requires-Dist: pytest==8.3.4
Requires-Dist: gliner==0.2.13

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# fraud
### Pronunciation: /frɔːd/ (FRAWD)

#### *Simplified Synthetic Data*

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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.

# Usage

Here's a basic example to get you started.

```python
import fraud as fr

synthetic_samples = fr.from_str('Could you please meet {name} at {time}', 20)
```

# Predicting Templates

Grab a sample from your dataset to make a template from it!

```python
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)
```
