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  • 无监督中文抽取式摘要

    Github : https://github.com/dmmiller612/bert-extractive-summarizer

    该git提供了一个中文无监督抽取关键句的方法,主要思想就是bert做向量表示,然后利用聚类计算距离。本文提供了中文的实现方法

    pip install bert-extractive-summarizer
    pip install spacy==2.3.1
    pip install transformers
    pip install neuralcoref
    python -m spacy download zh_core_web_lg #中文spacy
    import spacy
    import zh_core_web_lg
    import neuralcoref
    
    nlp = zh_core_web_lg.load()
    neuralcoref.add_to_pipe(nlp)
    
    # summarizer 中文模型
    from summarizer import Summarizer
    from summarizer.sentence_handler import SentenceHandler
    from spacy.lang.zh import Chinese
    from transformers import *
    
    # Load model, model config and tokenizer via Transformers
    modelName = "bert-base-chinese" 
    custom_config = AutoConfig.from_pretrained(modelName)
    custom_config.output_hidden_states=True
    custom_tokenizer = AutoTokenizer.from_pretrained(modelName)
    custom_model = AutoModel.from_pretrained(modelName, config=custom_config)
    
    model = Summarizer(
        custom_model=custom_model, 
        custom_tokenizer=custom_tokenizer,
        sentence_handler = SentenceHandler(language=Chinese)
        )
    body = "要摘要的文章"
    
    result = model(body)
    full = ''.join(result)
    print(full) # 摘要出來的句子
    函数参数
    model(
        body: str # The string body that you want to summarize
        ratio: float # The ratio of sentences that you want for the final summary
        min_length: int # Parameter to specify to remove sentences that are less than 40 characters
        max_length: int # Parameter to specify to remove sentences greater than the max length,
        num_sentences: Number of sentences to use. Overrides ratio if supplied.
    )
    

      

     
    我当记事本用的
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  • 原文地址:https://www.cnblogs.com/amazement/p/14905143.html
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