一、使用huggingface中的预训练模型，先要安装transformers、torch和SentencePiece
pip install transformers
pip install torch
pip install SentencePiece手动下载：https://huggingface.co/google-bert/bert-base-uncased/tree/main
添加以目录：
二、运行代码
from transformers import BertTokenizer, BertForSequenceClassification, pipeline
# 加载预训练的模型和分词器
model_name = 'bert-base-uncased'
tokenizer = BertTokenizer.from_pretrained(model_name)
model = BertForSequenceClassification.from_pretrained(model_name, num_labels=2) # 假设是二分类问题
# 使用pipeline简化流程
classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
# 文本分类
text = "I hate this movie!"
result = classifier(text)
print(result)输入：I hate unnecessary waste
输出结果：
输入：I love dance!
输出：
