Really great question I have been using the below method, passing dimension into softmax is required if you’re looking to get for example class probabilities of a whole batch- (tensor <=2D)  as in <=2D numpy array the dimension is required.
with torch.no_grad():
    model.eval()
    for data, label in tqdm(test_loader):
            data = data.to(device)
            label = label.to(device)
            output = model(data)            
            sm = torch.nn.Softmax(dim=1)
            probabilities = sm(output)

Hope this helps [[  ],[  ]]