Phi-3, is a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks. The Phi-3 Family includes mini, small, medium and vision versions, trained based on different parameter amounts to serve various application scenarios. For more detailed information about Microsoft's Phi-3 family, please visit the Welcome to the Phi-3 Family page.

• Introduction

  • Setting up your environment(✅)
  • Welcome to the Phi-3 Family(✅)
  • Understanding Key Technologies(✅)
  • AI Safety for Phi-3 Models(✅)
  • Phi-3 Hardware Support(✅)
  • Phi-3 Models & Availability across platforms(✅)

• Quick Start

  • Using Phi-3 in Hugging face(✅)
  • Using Phi-3 in Azure AI Studio(✅)
  • Deploying Phi-3 models as serverless APIs in Azure AI Studio(✅)
  • Using Phi-3 in Ollama(✅)
  • Using Phi-3 in LM Studio(✅)
  • Using Phi-3 in AI Toolkit VSCode(✅)

• Inference Phi-3

  • Inference Phi-3 in iOS(✅)
  • Inference Phi-3 in Jetson(✅)
  • Inference Phi-3 in AI PC(✅)
  • Inference Phi-3 with Apple MLX Framework(✅)
  • Inference Phi-3 in Local Server(✅)
  • Inference Phi-3 in Remote Server using AI Toolkit(✅)
  • Inference Phi-3 with Rust(✅)
  • Inference Phi-3-Vision in Local(✅)

• Fine-tuning Phi-3

  • Downloading & Creating Sample Data Set(✅)
  • Fine-tuning Scenarios(✅)
  • Fine-tuning vs RAG(✅)
  • Fine-tuning Let Phi-3 become an industry expert(✅)
  • Fine-tuning Phi-3 with AI Toolkit for VS Code(✅)
  • Fine-tuning Phi-3 with Azure Machine Learning Service(✅)
  • Fine-tuning Phi-3 with Lora(✅)
  • Fine-tuning Phi-3 with QLora(✅)
  • Fine-tuning Phi-3 with Azure AI Studio(✅)
  • Fine-tuning Phi-3 with Azure ML CLI/SDK(✅)
  • Fine-tuning with Microsoft Olive(✅)
  • Fine-tuning Phi-3-vision with Weights and Bias(✅)
  • Fine-tuning Phi-3 with Apple MLX Framework(✅)
  • Fine-tuning Phi-3-vision (official support)(✅)

• Evaluation Phi-3

  • Introduction to Responsible AI(✅)
  • Introduction to Promptflow(✅)
  • Introduction to Azure AI Studio for evaluation(✅)

• E2E Samples for Phi-3-mini

  • Introduction to End to End Samples(✅)
  • Prepare your industry data(✅)
  • Use Microsoft Olive to architect your projects(✅)
  • Inference Your Fine-tuning ONNX Runtime Model(✅)
  • Multi Model - Interactive Phi-3-mini and OpenAI Whisper(✅)
  • MLFlow - Building a wrapper and using Phi-3 with MLFlow(✅)
  • WinUI3 App with Phi-3 mini-4k-instruct-onnx(✅)
  • WinUI3 Multi Model AI Powered Notes App Sample(✅)
  • Fine-tune and Integrate custom Phi-3 models with Prompt flow(✅)

• E2E Samples for Phi-3-vision

  • Phi-3-vision-Image text to text(✅)
  • Phi-3-vision-ONNX(✅)
  • Phi-3-vision CLIP Embedding(✅)

• Labs and workshops samples Phi-3

  • C# .NET Labs(✅)
  • Build your own Visual Studio Code GitHub Copilot Chat with Microsoft Phi-3 Family(✅)
  • Phi-3 ONNX Tutorial(✅)
  • Phi-3-vision ONNX Tutorial(✅)
  • Run the Phi-3 models with the ONNX Runtime generate() API(✅)
  • Phi-3 ONNX Multi Model LLM Chat UI, This is a chat demo(✅)
  • C# Hello Phi-3 ONNX example Phi-3(✅)
  • C# API Phi-3 ONNX example to support Phi3-Vision(✅)
  • Run C# Phi-3 samples in a CodeSpace(✅)
  • Using Phi-3 with Promptflow and Azure AI Search(✅)

You can learn how to use Microsoft Phi-3 and how to build E2E solutions in your different hardware devices. To experience Phi-3 for yourself, start by playing with the model and customizing Phi-3 for your scenarios using the Azure AI Studio, Azure AI Model Catalog

Playground Each model has a dedicated playground to test the model Azure AI Playground.

You can also find the model on the Hugging Face

Playground Hugging Chat playground

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