Thank you! This is the call I make now:
with torch.no_grad():
    pred = []
    for idx, sl in tqdm(enumerate(ct), total=ct.shape[0]):
        tensor = torch.unsqueeze(torch.from_numpy(sl.transpose(2,0,1)), 0)
        pred.append(model(Variable(tensor.cuda())))
    vol_pred = torch.cat(pred, 0)