GPT 3.5 Fine Tuning Just Announced - Everything You Need to Know

Overview

Explore the newly announced GPT-3.5 fine-tuning capabilities in this comprehensive video tutorial. Delve into the implications of this update, examining the fine-tuning data format, API calls, and step-by-step processes. Learn about pricing, data preparation, cost estimation, and practical Python code implementation. Gain insights on improving datasets, explore fine-tuning examples, and generate Python code for API calls using the Playground. Cover frequently asked questions and access additional resources, including links to related videos and documentation, to enhance your understanding of GPT-3.5 fine-tuning.

Syllabus

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Intro
My older fine tuning video with examples
Continuing reading the blog post
Fine tuning data format
Continuing reading the blog post
reexamining fine tuning data format
Continuing reading the blog post
example API call
Fine Tuning Steps
Pricing
Looking at Fine Tuning documentation
Preparing Fine Tuning data
How much data do I need?
How to estimate costs
Python code for Fine Tuning
My example Fine Tuning video with legacy models
gpt llm trainer repo
How do I use a fine tuned model?
How to improve the dataset
Fine Tuning examples
Generate Python code for API call with Playground
FAQ