| # how to use | |
| ```python | |
| # !pip install transformers | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| from huggingface_hub import PyTorchModelHubMixin | |
| class Net(nn.Module,PyTorchModelHubMixin): | |
| def __init__(self): | |
| super().__init__() | |
| self.conv1 = nn.Conv2d(3, 6, 5) | |
| self.pool = nn.MaxPool2d(2, 2) | |
| self.conv2 = nn.Conv2d(6, 16, 5) | |
| self.fc1 = nn.Linear(16 * 5 * 5, 120) | |
| self.fc2 = nn.Linear(120, 84) | |
| self.fc3 = nn.Linear(84, 10) | |
| def forward(self, x): | |
| x = self.pool(F.relu(self.conv1(x))) | |
| x = self.pool(F.relu(self.conv2(x))) | |
| x = torch.flatten(x, 1) # flatten all dimensions except batch | |
| x = F.relu(self.fc1(x)) | |
| x = F.relu(self.fc2(x)) | |
| x = self.fc3(x) | |
| return x | |
| net = Net.from_pretrained('Adapting/cifar10-image-classification') | |
| ``` | |
| example codes for testing the model: [link](https://colab.research.google.com/drive/10xjbgSzw-U1Y4vCot5aqqdOi7AhmIkC3?usp=sharing) |