Kyle Corbitt, CEO OpenPipe: How to Fine-Tune Your Own Language Model (LLM)

ConTejas Code

Links

- Codecrafters (Sponsor): https://tej.as/codecrafters

- Wix (Sponsor): https://tej.as/wix

- OpenPipe: https://openpipe.ai

- Kyle on X: https://x.com/corbtt

- Tejas on X: https://x.com/tejaskumar_

Summary

Kyle Corbitt, founder and CEO of OpenPipe, shares the origin story of the company and his background in computer science and entrepreneurship. He discusses the evolution of machine learning and the breakthroughs that made OpenPipe possible. The conversation then dives into the process of fine-tuning models using OpenPipe, including the logging feature, data curation, and the selection of base models and hyperparameters.

The episode also explores the developer experience and the decision to create an SDK that is a drop-in replacement for the OpenAI SDK. The conversation explores the concept of overfitting in machine learning models and how it differs for language models. The validation process for fine-tuned models is discussed, including inner loop tests and outer loop evaluations.

Takeaways

1. OpenPipe was founded to help people transition easily and smoothly into fine-tuning models using machine learning.

2. The process of fine-tuning models involves logging user requests, curating data, selecting base models, and optimizing hyperparameters.

3. OpenPipe provides an SDK that is a drop-in replacement for the OpenAI SDK, making it easy for developers to integrate OpenPipe into their existing workflows.

4. The platform automates the heavy lifting of fine-tuning models, including the optimization of hyperparameters based on thousands of fine-tuned models and user-defined evaluations.

5. OpenPipe offers a seamless developer experience, allowing users to quickly and efficiently fine-tune models and deploy them for production use.

Chapters

00:00 Kyle Corbitt

03:28 The Origin Story of OpenPipe

14:34 Fine-Tuning Models with OpenPipe

33:46 Understanding Overfitting and Fine-Tuning

39:47 The Role of Hyperparameters

46:32 Validating Fine-Tuned Models

56:46 Enabling Tool Calls in Language Models

01:00:33 Unleashing the Full Potential of Language Models

01:05:09 Introduction to OpenPipe

01:10:14 Changing the Configuration Parameter

01:20:17 The Future of OpenPipe

01:25:31 The Need for a Founder's Handbook

01:32:17 Advice for Technical Founders and CEOs

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