Phi Cookbook: Hands-On Examples with Microsoft's Phi Models

Phi is a series of open source AI models developed by Microsoft.

Phi is currently the most powerful and cost-effective small language model (SLM), with very good benchmarks in multi-language, reasoning, text/chat generation,coding, images, audio and other scenarios.

You can deploy Phi to the cloud or to edge devices, and you can easily build generative AI applications with limited computing power.

Follow these steps to get started using these resource :

1. Fork the Repository: Click
2. Clone the Repository: git clone https://github.com/microsoft/PhiCookBook.git
3. Join The Microsoft AI Discord Community and meet experts and fellow developers

🌐 Multi-Language Support

Supported via GitHub Action (Automated & Always Up-to-Date)

<!-- CO-OP TRANSLATOR LANGUAGES TABLE START -->

Arabic | Bengali | Bulgarian | Burmese (Myanmar) | Chinese (Simplified) | Chinese (Traditional, Hong Kong) | Chinese (Traditional, Macau) | Chinese (Traditional, Taiwan) | Croatian | Czech | Danish | Dutch | Estonian | Finnish | French | German | Greek | Hebrew | Hindi | Hungarian | Indonesian | Italian | Japanese | Kannada | Korean | Lithuanian | Malay | Malayalam | Marathi | Nepali | Nigerian Pidgin | Norwegian | Persian (Farsi) | Polish | Portuguese (Brazil) | Portuguese (Portugal) | Punjabi (Gurmukhi) | Romanian | Russian | Serbian (Cyrillic) | Slovak | Slovenian | Spanish | Swahili | Swedish | Tagalog (Filipino) | Tamil | Telugu | Thai | Turkish | Ukrainian | Urdu | Vietnamese

Prefer to Clone Locally?

This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:

Bash / macOS / Linux:

git clone --filter=blob:none --sparse https://github.com/microsoft/PhiCookBook.git
cd PhiCookBook
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'

CMD (Windows):

git clone --filter=blob:none --sparse https://github.com/microsoft/PhiCookBook.git
cd PhiCookBook
git sparse-checkout set --no-cone "/*" "!translations" "!translated_images"

This gives you everything you need to complete the course with a much faster download.

<!-- CO-OP TRANSLATOR LANGUAGES TABLE END -->

Table of Contents

• Introduction

  • Welcome to the Phi Family
  • Setting up your environment
  • Understanding Key Technologies
  • AI Safety for Phi Models
  • Phi Hardware Support
  • Phi Models & Availability across platforms
  • Using Guidance-ai and Phi
  • GitHub Marketplace Models
  • Azure AI Model Catalog

• Inference Phi in different environment

  • Hugging face
  • GitHub Models
  • Microsoft Foundry Model Catalog
  • Ollama
  • AI Toolkit VSCode (AITK)
  • NVIDIA NIM
  • Foundry Local

• Inference Phi Family

  • Inference Phi in iOS
  • Inference Phi in Android
  • Inference Phi in Jetson
  • Inference Phi in AI PC
  • Inference Phi with Apple MLX Framework
  • Inference Phi in Local Server
  • Inference Phi in Remote Server using AI Toolkit
  • Inference Phi with Rust
  • Inference Phi--Vision in Local
  • Inference Phi with Kaito AKS, Azure Containers(official support)

• Quantifying Phi Family

  • Quantizing Phi-3.5 / 4 using llama.cpp
  • Quantizing Phi-3.5 / 4 using Generative AI extensions for onnxruntime
  • Quantizing Phi-3.5 / 4 using Intel OpenVINO
  • Quantizing Phi-3.5 / 4 using Apple MLX Framework

• Evaluation Phi

  • Response AI
  • Microsoft Foundry for Evaluation
  • Using Promptflow for Evaluation

• RAG with Azure AI Search

  • How to use Phi-4-mini and Phi-4-multimodal(RAG) with Azure AI Search

• Phi application development samples

  • Text & Chat Applications
    • Phi-4 Samples
      • [📓] Chat With Phi-4-mini ONNX Model
      • Chat with Phi-4 local ONNX Model .NET
      • Chat .NET Console App with Phi-4 ONNX using Sementic Kernel
    • Phi-3 / 3.5 Samples
      • Local Chatbot in the browser using Phi3, ONNX Runtime Web and WebGPU
      • OpenVino Chat
      • Multi Model - Interactive Phi-3-mini and OpenAI Whisper
      • [MLFlow - Buildin