/Fine-Tune-and-Integrate-Custom-Phi-3-Models-with-Prompt-Flow

This is a code example from the "Fine-Tune and Integrate Custom Phi-3 Models with Prompt Flow" tutorial published on the Microsoft Tech Community.

Primary LanguagePython

Fine-Tune-and-Integrate-Custom-Phi-3-Models-with-Prompt-Flow

This is a code example from the "Fine-Tune and Integrate Custom Phi-3 Models with Prompt Flow" tutorial published on the Microsoft Tech Community.

Introduction

Phi-3 is a family of small language models (SLMs) developed by Microsoft that delivers exceptional performance and cost-effectiveness. In this tutorial, you will learn how to fine-tune the Phi-3 model and integrate it with Prompt Flow. By leveraging Azure Machine Learning, and Prompt flow you will establish a workflow for deploying and utilizing custom AI models. This tutorial is divided into three series:

  1. Series 1: Set up Azure resources and Prepare the Environment

    • In Series 1, You will learn how to configure the necessary Azure resources and set up your environment for model fine-tuning.

  2. Series 2: Fine-Tune and Deploy the Phi-3 model

    • In Series 2, you will fine-tune the Phi-3 model. After fine-tuning, you will deploy the model, making it accessible for integration with Prompt Flow.

  3. Series 3: Integrate the custom phi-3 model with Prompt Flow

    • In Series 3, You will Integrate the fine-tuned Phi-3 model with Prompt flow.

Here is an overview of this tutorial.

00-1-architecture

Reference