def METHOD_NAME(self,
                inputs: Dict[str, Any],
                candidate_labels,
                multi_label=False) -> Dict[str, Any]:
    """process the prediction results
    Args:
        inputs (Dict[str, Any]): _description_
    Returns:
        Dict[str, Any]: the prediction results
    """
    logits = inputs[OutputKeys.LOGITS].cpu().numpy()
    if multi_label or len(candidate_labels) == 1:
        logits = logits[..., [self.contradiction_id, self.entailment_id]]
        scores = softmax(logits, axis=-1)[..., 1]
    else:
        logits = logits[..., self.entailment_id]
        scores = softmax(logits, axis=-1)
    reversed_index = list(reversed(scores.argsort()))
    result = {
        OutputKeys.LABELS: [candidate_labels[i] for i in reversed_index],
        OutputKeys.SCORES: [scores[i].item() for i in reversed_index],
    }
    return result