我们如何从huggingface转换器问题答案的示例代码中获取答案置信度得分？我看到管道确实返回了分数，但是下面的核心也可以返回置信度分数吗？
\nfrom transformers import AutoTokenizer, TFAutoModelForQuestionAnswering\nimport tensorflow as tf\n\ntokenizer = AutoTokenizer.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")\nmodel = TFAutoModelForQuestionAnswering.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")\n\ntext = r"""\n Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides general-purpose\narchitectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet\xe2\x80\xa6) for Natural Language Understanding (NLU) and Natural\nLanguage Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between\nTensorFlow 2.0 and PyTorch.\n"""\n\nquestions = [\n "How many pretrained models are available in Transformers?",\n "What does Transformers provide?",\n "Transformers provides interoperability between which frameworks?",\n]\n\nfor question in questions:\n inputs = …