Cifar Cnn
A 3-block CNN trained from scratch on CIFAR-10 using PyTorch.
Model source
- Kind
- Other
- File size
- 5.13 MB
- Version
- vRevision f2bb2f9
- Updated
- Oct 11, 2026
- Downloads
- 5
- Source
- Hugging Face
Source description
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}]
Sources
1 source
Sources
1 sourceVerified Aug 26
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- 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}] ```
Source context: 5 downloads · 0 likes · Pipeline image-classification · Repo MarkivDunhar/cifar-cnn
