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cnn-cifar10

Image Classification
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metadata
license: mit
pipeline_tag: image-classification

ResNet-20 model for CIFAR-10

This is the repo for a custom-made neural network based on ResNet architecture that has been trained on CIFAR-10 dataset.

Model details

  • Architecture: ResNet
  • Input shape: 3x32x32
  • Output classes: 10
  • Parameters: 272,474
  • Dataset: CIFAR-10

More details can be found in the config.json file inside this repository and the original git repository from which the model originated.

Model usage

Since the model for which the weights loaded in this repository are intended is a part of a custom Python package, one needs to firstly clone the project locally:

git clone https://github.com/spolivin/cifar10-website.git
cd cifar10-website/nn_dev

Next, in a Python script we can make imports and load the weights:

import torch

from pytorch_models import resnet20

# URL from which to load the weights
URL = "https://huggingface.co/spolivin/cnn-cifar10/resolve/main/resnet20_weights.pth"

# Building the ResNet-20 model
resnet20_model = resnet20()

# Loading the pretrained weights to the model
resnet20_model.load_state_dict(
        torch.hub.load_state_dict_from_url(
            url=URL,
            weights_only=True,
            map_location=torch.device("cpu"),
        )
    )