sugardata 0.0.4

Generates synthetic datasets tailored for transformer-based models

sugardata

sugardata is a Python package that helps you generate synthetic datasets for NLP tasks, enabling experimentation, prototyping, and training when labeled data is limited or unavailable.

Installation

You can install sugardata via pip:

pip install sugardata

Quick Start

sugardata supports multiple NLP tasks out of the box.

Task 1: Sentiment Analysis

import sugardata as su

# generate synchronously
results = su.generate_sentiment_data(concept="online shopping")

# generate asynchronously
results = await su.generate_sentiment_data_async(concept="online shopping")

# generate concurrently with multiple vendor
results = await su.generate_sentiment_multi_vendor_async(concept="online shopping")

# augment synchronously
examples = [
    # some text
    ...
]

results = su.augment_sentiment_data(examples=examples)

# augment asynchronously
results = await su.augment_sentiment_data_async(examples=examples)

# augment concurrently with multiple vendor
results = await su.augment_sentiment_multi_vendor_async(examples=examples)

To learn more about configuration options, advanced parameters, and integration tips, please visit tutorials.