torch.cuda.FloatTensor is a normal FloatTensor, but it is on a GPU. The only problem is that it is a different type, so if you have a model in cpu, you cannot assign to it cuda tensors.
So you either bring the model to GPU and then load it (and potentially reconvert the loaded model to cpu), or you convert the cuda tensors in the state dict to normal tensors. Something like this should work
cpu_model_dict = {}
for key, val in model_dict.items():
    cpu_model_dict[key] = val.cpu()