src/transformers/pipelines/audio_classification.py/AudioClassificationPipeline/postprocess
class AudioClassificationPipeline:    def postprocess(self, model_outputs, top_k=5):
        probs = model_outputs.logits[0].softmax(-1)
        scores, ids = probs.topk(top_k)

        scores = scores.tolist()
        ids = ids.tolist()

        labels = [{"score": score, "label": self.model.config.id2label[_id]} for score, _id in zip(scores, ids)]

        return labels