MarkivDunhar/cifar-cnn

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}]