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LLMs

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

Gretel Navigatorā€™s synthetic data generation outperformed OpenAI's GPT-4 by 25.6%, surpassed Llama3-70b by 48.1%, and exceeded human expert-curated data by 73.6%.
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Fine-Tuning CodeLlama on Gretel's Synthetic Text-to-SQL Dataset using Amazon SageMaker JumpStart

Fine-tune CodeLlama with Gretel's Synthetic Text-to-SQL on BIRDBench, achieving a 36% relative improvement in EX and 38% in VES.
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Fine-Tuning Gretel Navigator To Generate Highest Quality Domain-Specific Synthetic Data

Gretel Navigator now enables fine tuning for tabular datasets containing numeric, categorical, free text, JSON, and sequential (time series) data.
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Generate textbook-quality synthetic data for training LLMs and SLMs

How to use Gretel Navigator for generating diverse, high-quality training data to create better language models.
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Gretel announces partnership with Databricks

Gretel partners with Databricks to seamlessly integrate synthetic data workflows and improve model performance for Enterprise AI.
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Nail Synthetic Data Generation Every Time with Gretel Tuner

Automate hyperparameter sweeps to create the best synthetic data for your task šŸ§¹
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Filling in sparse tables with Gretel Navigator

How to automatically generate missing tabular data that maintains contextual relevance.
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Differential Privacy and Synthetic Text Generation with Gretel: Making Data Available at Scale (Part 1)

How differential privacy can generate provably private synthetic text data for a variety of enterprise AI applications.
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How to Improve RAG Model Performance with Synthetic Data

Effective strategies for leveraging high-quality synthetic data to improve RAG model performance.
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