Phi-1

Microsoft Research · June 2023

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Why It Matters

Launched Microsoft's 'small but mighty' research program, demonstrating that training data quality could be more important than model size — a finding that influenced the entire field.

Description

A tiny 1.3 billion parameter model focused on code generation, trained exclusively on 'textbook-quality' data — carefully curated examples designed to teach programming concepts clearly. Despite being over 100x smaller than GPT-4, it performed surprisingly well on coding benchmarks, proving that what a model learns from matters as much as its size.

Notable Milestones

  • ▸Proved textbook-quality data approach for code generation
  • ▸Inspired the 'small language model' movement

Key Innovations

Distillation
DistillationTraining a smaller 'student' model to mimic a larger 'teacher' model, preserving capability at lower cost.

Family Tree

Successors (1)

External Links