bert_cate/other/large.py

32 lines
987 B
Python

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:")