Phi Silica task specialization using LoRA in Microsoft Learning Zone: A technical deep dive

At Build 2025, we announced support for LoRA (low-rank-adaptation) finetuning for Phi Silica – our inbox Small Language Model (SLM) that runs locally on Copilot+ PCs. LoRA makes fine-tuning more efficient by updating only a small subset of parameters of the model with custom data. This allows improved performance on desired tasks without affecting model’s overall abilities.

This post shares the behind-the-scenes work and design considerations that enabled us to customize generation for a real-world use case: generating high-quality, pedagogically valuable Kahoot! quizzes. Our efforts led to a 75% reduction in rejection rates and show a 4.6X uplift in subjective quality scores.