phi-2

Maintainer: SkunkworksAI

Total Score

132

Last updated 5/28/2024

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PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

phi-2 is a 2.7 billion parameter language model from Microsoft's Skunkworks AI team. It builds upon their previous phi-1.5 model, using the same data sources augmented with new synthetic data and filtered web content. When tested on benchmarks of common sense, language understanding, and logical reasoning, phi-2 demonstrated state-of-the-art performance among models under 13 billion parameters.

Unlike phi-1.5, phi-2 has not been fine-tuned for instruction following or through reinforcement learning from human feedback. Instead, the goal is to provide the research community with a non-restricted small model to explore safety challenges like reducing toxicity, understanding biases, and enhancing controllability.

Model inputs and outputs

Inputs

  • Text prompts in a variety of formats, including question-answer, chat, and code

Outputs

  • Generated text responses to the input prompts

Capabilities

phi-2 exhibits strong performance on language tasks like question answering, dialogue, and code generation. However, it may produce inaccurate statements or code snippets, so users should treat the outputs as starting points rather than definitive solutions. The model also struggles with adhering to complex instructions, as it has not been fine-tuned for this purpose.

What can I use it for?

As an open-source research model, phi-2 is intended for exploring model safety and capabilities, rather than direct deployment in production applications. Researchers can use it to study techniques for reducing toxicity, mitigating biases, and improving controllability of language models. Developers may also find it useful as a building block for prototyping conversational AI features, though they should be cautious about relying on the model's outputs without thorough verification.

Things to try

One interesting aspect of phi-2 is its ability to generate code in response to prompts. Developers can experiment with giving the model code-related prompts, such as asking it to write a function to solve a specific problem. However, they should be mindful of the model's limitations in this area and verify the generated code before using it.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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