Phi-4 Model Card Hugging Face

 Phi-4 Model Card

Phi-4 Technical Report microsoft/phi-4 · Hugging Face

Model Summary

Developers Microsoft Research

Description phi-4 is a state-of-the-art open model built upon a blend of synthetic datasets, data from filtered public domain websites, and acquired academic books and Q&A datasets. The goal of this approach was to ensure that small capable models were trained with data focused on high quality and advanced reasoning.

phi-4 underwent a rigorous enhancement and alignment process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures

Architecture 14B parameters, dense decoder-only Transformer model

Inputs Text, best suited for prompts in the chat format

Context length 16K tokens

GPUs 1920 H100-80G

Training time 21 days

Training data 9.8T tokens

Outputs Generated text in response to input

Dates October 2024 – November 2024

Status Static model trained on an offline dataset with cutoff dates of June 2024 and earlier for publicly available data

Release date December 12, 2024

License MIT

microsoft/phi-4 · Hugging Face

https://huggingface.co/microsoft/phi-4#:~:text=phi-4%20is%20a%20state-of-the-art%20open%20model%20built%20upon,websites%2C%20and%20acquired%20academic%20books%20and%20Q%26A%20datasets.

Quick Links

Inference Providers documentation

Nebius AI Studio documentation

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microsoft/phi-4 · Hugging Face

import os

from openai import OpenAI

client = OpenAI(

    base_url="https://router.huggingface.co/v1",

    api_key=os.environ["HF_TOKEN"],

)

completion = client.chat.completions.create(

    model="microsoft/phi-4:nebius",

    messages=[

        {

            "role": "user",

            "content": "What is the capital of France?"

        }

    ],

)

print(completion.choices[0].message)

-----------------------------

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