Dive into an in-depth video lecture featuring Kyle Corbitt, CEO of OpenPipe, as he explores the intricacies of fine-tuning language models (LLMs). Learn about the origins of OpenPipe, the evolution of machine learning, and the process of fine-tuning models using their platform. Discover the importance of data curation, base model selection, and hyperparameter optimization. Explore the developer experience, including OpenPipe's SDK that seamlessly integrates with existing OpenAI workflows. Gain insights into overfitting in language models, validation processes, and enabling tool calls. Understand the future potential of LLMs and receive valuable advice for technical founders and CEOs in the AI space.
Overview
Syllabus
Kyle Corbitt
The Origin Story of OpenPipe
Fine-Tuning Models with OpenPipe
Understanding Overfitting and Fine-Tuning
The Role of Hyperparameters
Validating Fine-Tuned Models
Enabling Tool Calls in Language Models
Unleashing the Full Potential of Language Models
Introduction to OpenPipe
Changing the Configuration Parameter
The Future of OpenPipe
The Need for a Founder's Handbook
Advice for Technical Founders and CEOs
Taught by
Tejas Kumar
