HomeWinBuzzer NewsMicrosoft's New Phi-1.5 1.3B Model Outperforms llama2-7b in Benchmarks

Microsoft’s New Phi-1.5 1.3B Model Outperforms llama2-7b in Benchmarks

Microsoft Research has unveiled phi-1.5, a large language model (LLM) that is designed to excel in a variety of formats, including QA, chat, and code.


has unveiled its newest addition to the world of language models: phi-1.5. Designed to excel in a variety of formats, including QA, chat, and code, this Transformer-based model is equipped with 1.3 billion parameters. It's trained on a rich blend of data, from Python codes sourced from StackOverflow to exercises inspired by gpt-3.5-turbo-0301.

Performance Metrics in the Spotlight

When it comes to performance, phi-1.5 matches up well to rival large language models. The model competes favorably in its category, showcasing impressive results, especially when compared to models with similar parameters. In benchmark evaluations, phi-1.5 not only matched but in some instances, surpassed the capabilities of models like Meta's llama-2 7b, especially in the AGIEval score and the GPT4ALL's Benchmark suite.

Embracing the Open-Source Ethos

In a move that resonates with the broader tech community's ethos, has released phi-1.5 as an open-source model. The goal? To foster collaboration and provide researchers worldwide with a versatile tool to tackle pressing challenges in , bias mitigation, and more.

For enthusiasts looking for a deeper understanding, Hugging Face provides an in-depth look at phi-1.5. The model's training strategy is an evolution from its predecessor, phi-1, enriched with a new data source brimming with NLP synthetic texts. While the model is a powerhouse in its own right, it steers clear of certain training methods, such as instruction following or reinforcement learning from human feedback.

A technical report published on ArXiv offers further insights into the model's development. The emphasis has been on harnessing the power of common sense reasoning in natural language. Phi-1.5, while reflecting some characteristics of larger LLMs, brings to the table unique strengths, especially in the domain of safety, by consciously omitting web data during its training phase.

Luke Jones
Luke Jones
Luke has been writing about all things tech for more than five years. He is following Microsoft closely to bring you the latest news about Windows, Office, Azure, Skype, HoloLens and all the rest of their products.

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