Introducing Phi-3: Redefining what’s potential with SLMs

We’re excited to introduce Phi-3, a household of open AI fashions developed by Microsoft. Phi-3 fashions are the most succesful and cost-effective small language fashions (SLMs) obtainable, outperforming fashions of the identical dimension and subsequent dimension up throughout a wide range of language, reasoning, coding, and math benchmarks. This launch expands the collection of high-quality fashions for patrons, providing extra sensible selections as they compose and construct generative AI functions.

Beginning at present, Phi-3-mini, a 3.8B language mannequin is offered on Microsoft Azure AI Studio, Hugging Face, and Ollama

  • Phi-3-mini is offered in two context-length variants—4K and 128K tokens. It’s the first mannequin in its class to assist a context window of as much as 128K tokens, with little affect on high quality.
  • It’s instruction-tuned, that means that it’s skilled to comply with various kinds of directions reflecting how folks usually talk. This ensures the mannequin is able to use out-of-the-box.
  • It’s obtainable on Azure AI to make the most of the deploy-eval-finetune toolchain, and is offered on Ollama for builders to run domestically on their laptops.
  • It has been optimized for ONNX Runtime with assist for Home windows DirectML together with cross-platform assist throughout graphics processing unit (GPU), CPU, and even cell {hardware}.
  • It’s also obtainable as an NVIDIA NIM microservice with a normal API interface that may be deployed anyplace. And has been optimized for NVIDIA GPUs

Within the coming weeks, extra fashions might be added to Phi-3 household to supply clients much more flexibility throughout the quality-cost curve. Phi-3-small (7B) and Phi-3-medium (14B) might be obtainable within the Azure AI mannequin catalog and different mannequin gardens shortly.   

Microsoft continues to supply the most effective fashions throughout the quality-cost curve and at present’s Phi-3 launch expands the collection of fashions with state-of-the-art small fashions.

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Azure AI Studio

Phi-3-mini is now obtainable

Groundbreaking efficiency at a small dimension 

Phi-3 fashions considerably outperform language fashions of the identical and bigger sizes on key benchmarks (see benchmark numbers under, greater is healthier). Phi-3-mini does higher than fashions twice its dimension, and Phi-3-small and Phi-3-medium outperform a lot bigger fashions, together with GPT-3.5T.  

All reported numbers are produced with the identical pipeline to make sure that the numbers are comparable. Because of this, these numbers could differ from different revealed numbers as a consequence of slight variations within the analysis methodology. Extra particulars on benchmarks are offered in our technical paper

Word: Phi-3 fashions don’t carry out as properly on factual information benchmarks (similar to TriviaQA) because the smaller mannequin dimension ends in much less capability to retain information. 

Security-first mannequin design 

Phi-3 fashions had been developed in accordance with the Microsoft Accountable AI Customary, which is a company-wide set of necessities primarily based on the next six ideas: accountability, transparency, equity, reliability and security, privateness and safety, and inclusiveness. Phi-3 fashions underwent rigorous security measurement and analysis, red-teaming, delicate use overview, and adherence to safety steering to assist be certain that these fashions are responsibly developed, examined, and deployed in alignment with Microsoft’s requirements and greatest practices.  

Constructing on our prior work with Phi fashions (“Textbooks Are All You Want”), Phi-3 fashions are additionally skilled utilizing high-quality information. They had been additional improved with in depth security post-training, together with reinforcement studying from human suggestions (RLHF), automated testing and evaluations throughout dozens of hurt classes, and guide red-teaming. Our strategy to security coaching and evaluations are detailed in our technical paper, and we define really helpful makes use of and limitations within the mannequin playing cards. See the mannequin card assortment. 

Unlocking new capabilities 

Microsoft’s expertise transport copilots and enabling clients to remodel their companies with generative AI utilizing Azure AI has highlighted the rising want for different-size fashions throughout the quality-cost curve for various duties. Small language fashions, like Phi-3, are particularly nice for: 

  • Useful resource constrained environments together with on-device and offline inference eventualities.
  • Latency certain eventualities the place quick response occasions are important.
  • Price constrained use circumstances, notably these with less complicated duties.

For extra on small language fashions, see our Microsoft Supply Weblog.

Due to their smaller dimension, Phi-3 fashions can be utilized in compute-limited inference environments. Phi-3-mini, particularly, can be utilized on-device, particularly when additional optimized with ONNX Runtime for cross-platform availability. The smaller dimension of Phi-3 fashions additionally makes fine-tuning or customization simpler and extra reasonably priced. As well as, their decrease computational wants make them a decrease price possibility with a lot better latency. The longer context window allows taking in and reasoning over massive textual content content material—paperwork, internet pages, code, and extra. Phi-3-mini demonstrates robust reasoning and logic capabilities, making it a great candidate for analytical duties. 

Prospects are already constructing options with Phi-3. One instance the place Phi-3 is already demonstrating worth is in agriculture, the place web may not be readily accessible. Highly effective small fashions like Phi-3 together with Microsoft copilot templates can be found to farmers on the level of want and supply the extra good thing about operating at lowered price, making AI applied sciences much more accessible.  

ITC, a number one enterprise conglomerate primarily based in India, is leveraging Phi-3 as a part of their continued collaboration with Microsoft on the copilot for Krishi Mitra, a farmer-facing app that reaches over 1,000,000 farmers.

Our purpose with the Krishi Mitra copilot is to enhance effectivity whereas sustaining the accuracy of a big language mannequin. We’re excited to companion with Microsoft on utilizing fine-tuned variations of Phi-3 to fulfill each our targets—effectivity and accuracy!”   

Saif Naik, Head of Expertise, ITCMAARS

Originating in Microsoft Analysis, Phi fashions have been broadly used, with Phi-2 downloaded over 2 million occasions. The Phi collection of fashions have achieved outstanding efficiency with strategic information curation and progressive scaling. Beginning with Phi-1, a mannequin used for Python coding, to Phi-1.5, enhancing reasoning and understanding, after which to Phi-2, a 2.7 billion-parameter mannequin outperforming these as much as 25 occasions its dimension in language comprehension.1 Every iteration has leveraged high-quality coaching information and information switch methods to problem standard scaling legal guidelines. 

Get began at present 

To expertise Phi-3 for your self, begin with taking part in with the mannequin on Azure AI Playground. You may also discover the mannequin on the Hugging Chat playground. Begin constructing with and customizing Phi-3 in your eventualities utilizing the Azure AI Studio. Be part of us to study extra about Phi-3 throughout a particular dwell stream of the AI Present.  

1 Microsoft Analysis Weblog, Phi-2: The stunning energy of small language fashions, December 12, 2023.

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