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mnist-drawing-recognizer
ayzeksalimli/mnist-drawing-recognizer
mnist-drawing-recognizer is a image classification model from ayzeksalimli. Use it when you need a label for an image. It is set up for pytorch. The card lists the license as mit.
A lightweight CNN model for real-time handwritten digit recognition (0-9) with a PyQt5 drawing interface (see full project).
Access
Public
Updated May 8, 2026
Repo size
1.7 MB
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0
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Repo makeup
Click a slice to open those files.
.pth1.7 MB · 100%
At a glance
- Task
- Image Classification
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- May 8, 2026
- Updated
- May 8, 2026
- SHA
- 318add2d
Model card
From the Hugging Face model README
MNIST Drawing Recognizer
A lightweight CNN model for real-time handwritten digit recognition (0-9) with a PyQt5 drawing interface (see full project).
Model Description
- Architecture: Simple CNN with 2 convolutional layers + fully connected layers
- Framework: PyTorch
- Output: Digit 0-9 + confidence score
- Accuracy: ~98.7% on MNIST test set
Source Code
Full project: Click here!
Usage
from huggingface_hub import hf_hub_download
import torch
from train import Net
model_path = hf_hub_download("monadayzek/mnist-drawing-recognizer", "mnist_cnn.pth")
model = Net().to('cpu')
model.load_state_dict(torch.load(model_path, map_location='cpu', weights_only=True))
model.eval()
- Task
- Image Classification
- Library
- pytorch
- License
- mit
- Languages
- en, ru
- Created
- May 8, 2026
- Updated
- May 8, 2026