ONNX Model Zoo

Makatia/microsoft_Phi-3-mini-4k-instruct_onnx_rpi

By Makatia · ↓ 0 · ♥ 0 · Updated 2025-07-13

What's in this repo

This page lists the files in Makatia/microsoft_Phi-3-mini-4k-instruct_onnx_rpi.

  • No .onnx files in this repository
  • 3 files, including 1 .md, 1 .gz
  • Last updated 2025-07-13

ONNX files

This repository has no .onnx files. See the full file list on the right for other formats.

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

license: mit library_name: onnxruntime tags:

  • phi-3
  • onnx
  • quantized
  • rpi
  • edge-llm
  • local-inference model_creator: microsoft language: en

Phi-3 Mini 4K Instruct (ONNX, Raspberry Pi)

Efficient, quantized ONNX export of Phi-3 Mini 4K Instruct, optimized for local inference on resource-constrained devices like the Raspberry Pi.

📦 Model Overview

  • Archive: microsoft_Phi-3-mini-4k-instruct_onnx_rpi.tar.gz
  • Format: Quantized ONNX
  • Recommended for: ONNX Runtime, Kleidi AI, and similar frameworks

Unpack the archive to access the ONNX model and configuration files.

🚀 Quick Start

Install ONNX Runtime if you haven't already:

pip install onnxruntime

Run inference with the model:

import onnxruntime as ort

session = ort.InferenceSession("phi-3-mini-4k-instruct.onnx")
# Replace with your input and inference code

🛠️ Features

  • Optimized for Raspberry Pi: Low memory footprint and fast inference
  • Quantized: Reduced model size for edge deployment
  • Open Source: MIT licensed

📋 Credits

Maintainer: Makatia

Model info

onnxruntime
onnxruntime phi-3 onnx quantized rpi edge-llm local-inference en license:mit region:us
↓ 0 ♥ 0

Created: 2025-07-13

Updated: 2025-07-13

View on Hugging Face

Files (3)

.gitattributes
README.md
microsoft_Phi-3-mini-4k-instruct_onnx_rpi.tar.gz

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