Model Summary DevelopersMicrosoftGenAI DescriptionPhi-3 Miniis a lightweight, state-of-the-art open model built upon datasets used forPhi-2 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to thePhi-3model f...Phi-3 Miniis a powerful3.8B parameter model designed for advanced language understanding, reasoning, and instruction following. Optimized through supervised fine-tuning and preference adjustments, it excels in tasks involving common sense, mathematics, logical reasoning, and code processing.Attime of release,Phi-3Medium demonstrated state-of-the-art performance among lightweight models ...Apr 24, 2024 ·Phi-3 Mini Instructis an open-source, small language model developed byMicrosoftas part of thePhi-3family, positioned for both research and real-world practical applications. This model, formally known asPhi-3-Mini-128K-Instruct, features3.8 billion parameters and leverages an instruction-tuned, dense decoder-only Transformer architecture. Released initially in April 2024 and updated in ...Apr 10, 2026 ·Phi-3-mini-128k-instructis a3.8 billion-parameter dense decoder-only Transformer model built and maintained bymicrosoftfor commercial and research use...May 24, 2024 ·If you’re on a quest to supercharge your AI applications, understanding how to effectively utilize advanced language models like theMicrosoft Phi-3 Mini-128K Instructcan be a game changer. In this guide, we shall explore the intricacies of this lightweight, state-of-the-art model and how to harness its full potential. What isPhi-3 Mini-128K Instruct? ThePhi-3 Mini-128K Instructis a ...ThePhi-3-Mini-128K-Instructis a3.8 billion-parameter, lightweight, state-of-the-art open model trained using thePhi-3datasets. This dataset includes both synthetic data and filtered publicly available website data, with an emphasis on high-quality and reasoning-dense properties. After initial training, the model underwent a post-training process that involved supervised fine-tuning and ...

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