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microsoft/PhiCookBook resource

This is a Phi Family of SLMs book for getting started with Phi Models. Phi a family of open sourced AI models developed by Microsoft. Phi 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 observed · 2026-08-28

github.com/microsoft/PhiCookBook · Jupyter Notebook · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

69/100

  • Activity 99
  • Release rhythm 35
  • Longevity 60

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 848
  • days_rel: n/a
  • days_push: 7
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

3795 stars · 514 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A cookbook of hands-on Jupyter notebook examples and guides for Microsoft's Phi family of small language models (SLMs), covering Phi-3 and Phi-4 variants including multimodal and mini editions. It shows how to run, fine-tune, quantize, and deploy Phi models across cloud and edge devices.

Use cases

  • get started with microsoft phi small language models
  • run phi-4 on an edge device with limited compute
  • fine-tune phi-3 for a custom task
  • quantize phi models for on-device inference
  • learn to build generative ai apps with slms
  • run phi multimodal models on images and audio
  • deploy phi models to cloud or local hardware

When to choose

  • you want practical notebook-driven examples for Phi models specifically
  • you need to deploy capable small models on constrained hardware or edge devices
  • you want official, maintained guidance covering the Phi-3 and Phi-4 families including multimodal variants

When to avoid

  • you need a production serving framework rather than learning material
  • you are working with large frontier models like GPT or Llama-70B instead of SLMs
  • you want a general LLM course not focused on the Phi model family

Facets

learning-resource · maturity active

llm-inference machine-learning developer-tools large-language-models artificial-intelligence tutorials developer-tools python cross-platform cloud phi-models small-language-models cookbook jupyter-notebooks microsoft on-device-ai fine-tuning quantization

1 source

Member repositories

RepositoryRoleHealth v2
microsoft/PhiCookBookmain69

For agents

markdown · JSON · MCP: product_card(name="microsoft/PhiCookBook")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem