Metadata-Version: 2.1
Name: fraud
Version: 0.1.0
Summary: Add your description here
Project-URL: Homepage, https://github.com/yourusername/your-package
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
Provides-Extra: gliner
Requires-Dist: gliner==0.2.13; extra == "gliner"

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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. 

When finetuning for a domain specific task (i.e. extracting medical using NER), data scarcity can quickly become a limiting factor. Data annotation 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.make_fake('Could you please meet {name} at {time}', 20)
```
