C:\ProgramData\Anaconda3\envs\yolo\python.exe G:/nft/code/inference.py
Traceback (most recent call last):
File "G:/nft/code/inference.py", line 37, in
model = con.convnext_xlarge(pretrained=True, in_22k=True)
File "G:\nft\code\convnext.py", line 211, in convnext_xlarge
model.load_state_dict(checkpoint["model"])
File "C:\ProgramData\Anaconda3\envs\yolo\lib\site-packages\torch\nn\modules\module.py", line 1482, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for ConvNeXt:
size mismatch for head.weight: copying a param with shape torch.Size([21841, 2048]) from checkpoint, the shape in current model is torch.Size([1000, 2048]).
size mismatch for head.bias: copying a param with shape torch.Size([21841]) from checkpoint, the shape in current model is torch.Size([1000]).
C:\ProgramData\Anaconda3\envs\yolo\python.exe G:/nft/code/inference.py Traceback (most recent call last): File "G:/nft/code/inference.py", line 37, in
model = con.convnext_xlarge(pretrained=True, in_22k=True)
File "G:\nft\code\convnext.py", line 211, in convnext_xlarge
model.load_state_dict(checkpoint["model"])
File "C:\ProgramData\Anaconda3\envs\yolo\lib\site-packages\torch\nn\modules\module.py", line 1482, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for ConvNeXt:
size mismatch for head.weight: copying a param with shape torch.Size([21841, 2048]) from checkpoint, the shape in current model is torch.Size([1000, 2048]).
size mismatch for head.bias: copying a param with shape torch.Size([21841]) from checkpoint, the shape in current model is torch.Size([1000]).