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aplominski/
mnist-4.5k

Name: mnist-4.5k
Availability: InStock

image-classification

mit

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Lightweight MNIST CNN (4.5K Parameters)

This is an ultra-lightweight Convolutional Neural Network (CNN) with only 4.5K parameters, trained on the classic MNIST dataset for handwritten digit recognition.

Despite its minimal size, the model achieves 94.48% accuracy on the test split, making it highly efficient for edge devices or CPU-only environments.

The full training workflow and source code can be found on GitHub and weights can be found on Hugging Face

Model Performance

Task: Image Classification (Handwritten Digits 0-9)
Dataset: MNIST
Test Accuracy: 94.48%
Parameter Count: ~4,500

Quick Start / Usage

You can load and use this model directly using the code in github repository

aplominski/mnist-4.5k

Lightweight MNIST CNN (4.5K Parameters)

Model Performance

Quick Start / Usage

aplominski/
mnist-4.5k