metadata
license: apache-2.0
tags:
- image-classification
- pytorch
- cifar10
datasets:
- uoft-cs/cifar10
CIFAR-10 CNN Classifier
A 3-block CNN trained from scratch on CIFAR-10 using PyTorch.
Classes
plane, car, bird, cat, deer, dog, frog, horse, ship, truck
Training
- Architecture: 3× Conv blocks (32→64→128 channels) + FC classifier
- Optimizer: Adam + OneCycleLR scheduler
- Augmentation: RandomCrop, RandomFlip, ColorJitter, RandomErasing
- Validation accuracy: ~80%+ (after 64 epochs)
Usage
from transformers import pipeline
from PIL import Image
classifier = pipeline(
"image-classification",
model="MarkivDunhar/cifar-cnn"
)
result = classifier("your_image.jpg")
print(result)
# [{'label': 'dog', 'score': 0.91}]