---
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

```python
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}]
```