Maarten Van Segbroeck

Train financial LLMs with Gretel's Synthetic Text-to-Python dataset to transform natural language into precise, domain-specific Python code for FinTech.

Gretel fine-tuned, synthetically-enhanced GLiNER models for better PII & PHI detection—datasets included.

Gretel's latest open synthetic dataset aims to enhance LLM interactions and contributes to the popular 'awesome-chatGPT-prompts' GitHub repository.

Fine-tune CodeLlama with Gretel's Synthetic Text-to-SQL on BIRDBench, achieving a 36% relative improvement in EX and 38% in VES.

Leveraging Gretel Navigator to Create Diverse and Quality-Driven Question-Truth Pairs for RAG Evaluation

Use Gretel's synthetic data platform to replace, augment, or balance training datasets within MLOps pipelines like Vertex AI, Azure ML, and Amazon SageMaker.

Learn how to generate question-answer pairs from documents using a unique application built using Gretel Navigator.

Generate private and shareable data automatically by triggering Gretel jobs in Amazon SageMaker

Create high-quality synthetic datasets of conversational dialogs safely tuned on your private, sensitive data with Gretel.

Use Gretel DGAN and Gretel Tuner to generate time series data that accurately mirrors complex business rules and sequences