from transformers import pipeline


classifier = pipeline(
    "zero-shot-classification",
    model="./nlp_structbert_zero-shot-classification_chinese-large",
    device="cpu",
    max_length=512,
    ignore_mismatched_sizes=True  # 忽略维度不匹配警告
)
level1 = [
    "食品", "电器", "洗护", "女装", "手机",
    "健康", "男装", "美妆", "电脑", "运动",
    "内衣", "母婴", "数码", "百货", "鞋包",
    "办公", "家装", "饰品", "车品", "图书",
    "生鲜", "家纺", "宠物", "奢品", "其它","药品"
]


def theBestAndLow(goods):
    result = classifier(
        goods,
        candidate_labels=level1,
        truncation=True  # 显式指定截断策略
    )
    labels = result['labels']
    scores = result['scores']

    print("最高分标签:", labels[0], "得分:", scores[0])
    print("最低分标签:", labels[-1], "得分:", scores[-1])

theBestAndLow( "宇宙超萌儿童辅食有机果蔬蝴蝶面210g 数量:1盒装:")