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from torch import nn
import torchvision
import torch
def create_model(num_classes:int=3):
weights = torchvision.models.EfficientNet_B2_Weights.IMAGENET1K_V1
model=torchvision.models.efficientnet_b2(weights=weights)
transform=weights.transforms()
for param in model.parameters():
param.requires_grad=False
model.classifier=nn.Sequential(nn.Dropout(p=0.3, inplace=True),
nn.Linear(in_features=1408, out_features=num_classes, bias=True))
return model,transform
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