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Gadgets_model_save.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:90f169785198008285834c200c8258b84acfc1ad6244386f2d99e518663a3c7d
+size 95395709

model.py

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+import torch
+import torchvision
+
+from torch import nn
+
+
+def create_gadgets_model(num_classes:int=3, 
+                          seed:int=42):
+    # Create EffNetB2 pretrained weights, transforms and model
+    weights = torchvision.models.ResNet50_Weights.DEFAULT
+    transforms = weights.transforms()
+    model = torchvision.models.resnet50(weights=weights)
+
+    # Freeze all layers in base model
+    for param in model.parameters():
+        param.requires_grad = False
+
+    # Change classifier head with random seed for reproducibility
+    torch.manual_seed(seed)
+    model.fc = nn.Sequential(
+               nn.Linear(2048, 128),
+               nn.ReLU(inplace=True),
+               nn.Linear(in_features= 128,out_features=output_shape))
+    
+    return model, transforms

requirements.txt

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+torch==1.12.1
+torchvision==0.13.1
+gradio==3.4.1