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：