THX for the reply!
However, same error occurs although I used strict=False.

PATH = ‘/gdrive/My Drive/AIproject/epoch80.pt’
model.load_state_dict(torch.load(PATH), strict=False)

code below is structure of my Model

AlexNet2(
(layer1): Sequential(
(0): Conv2d(3, 96, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))
(1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): LeakyReLU(negative_slope=0.01, inplace=True)
(3): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
(4): Conv2d(96, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(5): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(6): LeakyReLU(negative_slope=0.01, inplace=True)
(7): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
(8): Conv2d(256, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(9): LeakyReLU(negative_slope=0.01, inplace=True)
(10): Conv2d(384, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(11): LeakyReLU(negative_slope=0.01, inplace=True)
(12): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(13): LeakyReLU(negative_slope=0.01, inplace=True)
(14): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
)
(fc): Sequential(
(0): Linear(in_features=2304, out_features=4096, bias=True)
(1): Dropout(p=0.4, inplace=False)
(2): Linear(in_features=4096, out_features=4096, bias=True)
(3): Dropout(p=0.4, inplace=False)
(4): Linear(in_features=4096, out_features=100, bias=True)
)
)

model I trained previously has almost same structure but it had 10 out_features at the last Linear array