Data Labeling Best Practices for Fine-Tuning LLMs

Data Labeling Best Practices for Fine-Tuning LLMs

Discover essential data labeling best practices in this lightning talk from the AI in Production Conference. Learn how to optimize your approach to fine-tuning open-source LLMs, covering key aspects such as hiring data labelers, preparing datasets, and effectively managing your labeling team. Gain insights from Charles Brecque, founder and CEO of TextMine, as he shares his expertise in leveraging knowledge graph technology and large language models for structuring unstructured data in documents. Explore strategies to enhance your LLM's performance and avoid common pitfalls in data labeling. This 13-minute presentation offers valuable knowledge for professionals working with AI and machine learning, particularly those involved in document processing and natural language understanding.