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# 使用这个类需要先安装库:pip install langchain-huggingface
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from langchain_huggingface import HuggingFaceEmbeddings
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# 指定模型名,如果你本地没有这个模型,第一次执行后它会先下载
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model_name = "BAAI/bge-small-zh-v1.5" # 模型名
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model_kwargs = {'device': 'cpu'} # 没有显卡就用cpu,有英伟达显卡写cuda
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encode_kwargs = {'normalize_embeddings': True} # set True to compute cosine similarity
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# 第一次运行,会自动下载模型(去huggingface上下载),下载到hf默认的缓存目录。
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hf_embedding = HuggingFaceEmbeddings(
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model_name=model_name,
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model_kwargs=model_kwargs,
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encode_kwargs=encode_kwargs
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)
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resp = hf_embedding.embed_documents(
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['I like large language models.',
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'今天的天气非常不错!'
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]
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)
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print(resp[0])
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print(len(resp[0]))
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