Curator is an open-source Python library designed to build synthetic data pipelines for training and evaluating machine learning models, particularly large language models. The system helps developers generate, transform, and curate high-quality datasets by combining automated generation with structured validation and filtering. It supports workflows where models are used to produce synthetic examples that can later be refined into reliable training datasets for reasoning, question answering, or structured information extraction tasks. Curator includes tools for monitoring data generation processes and managing dataset quality while large batches of examples are being created. The framework also integrates with multiple inference systems and APIs, allowing users to generate data using different model providers or open-source inference engines.

Features

  • Python library for creating synthetic training data pipelines
  • Support for structured output generation and dataset formatting
  • Interactive viewer for monitoring data generation workflows
  • Integration with multiple inference engines and APIs
  • Asynchronous processing and caching for large-scale pipelines
  • Fault-tolerant dataset generation and recovery mechanisms

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License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python Large Language Models (LLM)

Registered

2026-03-06