README.md

metadata

license: mit
language:
  - en
base_model:
  - unsloth/phi-4
  - microsoft/phi-4
pipeline_tag: text-generation

Phi-4 converted for ExLlamaV2

ExLlamaV2 is an inference library for running local LLMs on modern consumer GPUs.

Filename	Quant type	File Size	~Vram*
phi-4_hb8_3bpw	3.00 bits per weight	6.66 GB	10,3 GB
phi-4_hb8_4bpw	4.00 bits per weight	8.36 GB	11,9 GB
phi-4_hb8_5bpw	5.00 bits per weight	10.1 GB	13,5 GB
phi-4_hb8_6bpw	6.00 bits per weight	11.8 GB	15,1 GB
phi-4_hb8_7bpw	7.00 bits per weight	13.5 GB	16,7 GB
phi-4_hb8_8bpw	8.00 bits per weight	15.2 GB	18,2 GB

_{*approximate value at 16k context, FP16 cache.}

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Phi-4 Model Card

Phi-4 Technical Report

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
Context length	16384 tokens

Usage

Input Formats

Given the nature of the training data, phi-4 is best suited for prompts using the chat format as follows:

<|im_start|>system<|im_sep|>
You are a medieval knight and must provide explanations to modern people.<|im_end|>
<|im_start|>user<|im_sep|>
How should I explain the Internet?<|im_end|>
<|im_start|>assistant<|im_sep|>

With ExUI:

Add Phi-4 prompt format:

Edit/replace exui/backend/prompts.py with https://huggingface.co/cmh/phi-4_exl2/raw/main/backend/prompts.py