OpenAI GPT-3 finetuning is finaly here

A Comprehensive Guide to GPT-3.5 Turbo Fine-Tuning with Python Implementation

Unlock the power of OpenAI’s GPT-3 with this step-by-step guide on fine-tuning! Dive into Python code for seamless model training.

Illustration: Ruby Chen — Source: https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates

TL;DR

To fine-tune OpenAI’s GPT-3.5 Turbo:

1. Prepare Data: Format data as a series of interactions between the system, user, and assistant.
2. Upload Files: Use a curl command to send your data to OpenAI's API.
3. Initiate Fine-Tuning: Send another curl command using the uploaded data to start the fine-tuning process.
4. Use Fine-Tuned Model: Once done, use the fine-tuned model by sending a request to OpenAI’s chat completions endpoint.

This process customizes the GPT-3.5 Turbo model for specific tasks using your own data. For more information, you can read this post for Python implementation and full details or check out the OpenAI announcement:

GPT-3.5 Turbo fine-tuning and API updates

Before starting, if you want to learn more about generative AI, I suggest checking out my other posts using the below list:

Armin Norouzi, Ph.D

Generative AI

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Now, let’s get started!

Introduction

OpenAI, a leading organization in the field of artificial intelligence, has recently unveiled significant updates to its GPT-3.5 Turbo model. With these enhancements, developers can now fine-tune the model using their own data, allowing for more tailored and efficient applications. Additionally, this article provides easy-to-follow Python code to guide developers through the fine-tuning process. Dive in for an in-depth look into these updates, their benefits, and how you can leverage them for your…