Phi-2 Model
Deep Papers
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Training Small Coding Models with High-Quality Data Sets
The chapter explores the significance of training small coding models with high-quality data sets, focusing on specific components like filtered code language, synthetic textbook, and exercise data sets. It discusses the top performance achievable by small language models leveraging quality data, with an emphasis on diversity, randomness, and avoiding repetitive examples. Technical details of the Phi-2 model, its expansion into various domains, availability in Azure, benchmarks against Phi 1.5, and the decision not to use reinforcement learning are also covered.
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