It's the last day for these savings

LLM - Fine tune with custom data

Learn how to fine tune GPT 3.5 Turbo models using OpenAI, Gradient platforms with your own datasets

725 Students

5h23min

Beginner

4.5

thumbnail
  • Overview
  • Curriculum
  • Discussion
  • Review
  • Instructor

What you will learn

  • Understanding Fine tuning vs training data

  • Fine tune using GPT models, GPT 3.5 Turbo models, Open AI models

  • Preparing, creating, and uploading training and validation datasets

  • Fine tuning using Gradient Platform

  • Create Elon Mush Tweet Generator

  • Build a data extraction fine-tune model

What are the requirements for taking your course

  • Basic python knowledge

Who is this course for

  • Anyone who want to explore the world of AI

  • Anyone who want to step into AI world with practical fine tuning models

  • Data engineers, database administrators and data professionals curious about the emerging field of model fine tuning

  • Software developers interested in integrating their own data into large language models

  • Data scientists and machine learning engineers.

Description

Welcome to LLM - Fine Tune with Custom Data!


If you're passionate about taking your machine learning skills to the next level, this course is tailor-made for you. Get ready to embark on a learning journey that will empower you to fine-tune language models with custom datasets, unlocking a realm of possibilities for innovation and creativity.


Introduction to LLM and Fine Tuning


In this opening section, you'll be introduced to the course structure and objectives. We'll explore the significance of fine-tuning in enhancing language models and delve into the foundational models that set the stage for customization. Discover the reasons behind the need for fine-tuning and explore various strategies, including an understanding of critical model parameters. Gain a comprehensive understanding of the fundamental principles and advanced concepts in artificial intelligence and language modeling.


Fine Tune Using GPT Models


This section focuses on practical applications. Survey available models and their use cases, followed by essential steps in preparing and formatting sample data. Understand token counting and navigate potential pitfalls like warnings and cost management. Gain a comprehensive understanding of the fine-tuning process, differentiating between training and validation data. Learn to upload data to OpenAI, create a fine-tune job, and ensure quality assurance for your model.


Use Gradient Platform to quickly fine tune


Gradient AI Platform : The only AI Agent platform that supports fine-tuning, RAG development, and purpose built LLMs out-of-the-box. Pre-tuned, Domain Expert AI i.e. Gradient offers domain-specific AI designed for your industry. From healthcare to financial services, we've built AI from the ground up to understand domain context. Use the platform to upload and train base foundations models with your own dataset.


Create a Elon Musk Tweet Generator


Train a foundation model with Elon Mush sample tweets, and then used the 'New Fine Tune Model' to create Elon Mush style tweets. Create a streamlit app to demonstrate side-by-side a normal tweet generated by OpenAI vs your very own model.


Data Extraction fine-tune model


Learn how to extract 'valuable information' from a raw text. Learn how to pass sample datasets with question and answers, and then pass any raw text to get valuable information. Use real-world example of identifying person, amount spend and item from raw expense transactions and much more.


Enroll now to learn how to fine-tune large language models with your own data, and unlock the potential of personalized applications and innovations in the world of machine learning!

Introduction

What is fine-tuning?

Training vs Fine-tuning

The Foundation models

Why Fine-tune?

Ways to fine-tune a model

Model parameters

Fine tune using GPT models

Models availability, and use cases

Prepare the sample data

Format the sample data

Token counting function

Check warning and OpenAI cost

Understanding model fine-tuning

Training vs Validation data

Uploading training and validation data to OpenAI

Create a fine tune job

QA using your new model

Fine tune using gradient platform

Gradient platform - Setting up login

img

No Discussion Found

4.5

61 Reviews

5
36
4
15
3
8
2
2
1
0
Adnan Waheed

Instructor

$43.40

This Course Includes

51 Lessons
0 Quiz
0 Assignment
11 Downloadable Resources
English
Full Lifetime Access
Certificate of completion
Go To Class

Related Skills

More Courses From Jacob Collier

Udemy Udemy

LLM - Fine tune with custom data

725 students 5h23min