How to Create High Quality Synthetic Data for Fine-Tuning LLMs

Gretel Navigator is a compound AI system that enables users to easily create high-quality synthetic data for training AI and LLMs. It leverages agentic workflows, task planning, and multiple tools & models to iteratively review and improve synthetic data. Key features include evolutionary algorithms, multi-LM collaboration, agent-based generation, self-alignment, comprehensive governance, and customizable design. Gretel Navigator can generate a wide variety of synthetic data, including text, instruction-response pairs, step-by-step evaluation data, and question-answer pairs from documents. It has been shown to outperform its own underlying LLMs and even much larger models such as OpenAI's GPT-4.

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