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TensorFlow Hub 是一个训练好的机器学习模型库，可随时进行微调并部署到任何地方。只需几行代码即可重用 BERT 和 Faster R-CNN 等训练好的模型。
让我们加载 TensorflowHub Embedding 类。 
from langchain_community.embeddings import TensorflowHubEmbeddings

embeddings = TensorflowHubEmbeddings()

2023-01-30 23:53:01.652176: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-01-30 23:53:34.362802: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

text = "This is a test document."

query_result = embeddings.embed_query(text)

doc_results = embeddings.embed_documents(["foo"])

doc_results
在 GitHub 上编辑此页面源文件。
以编程方式连接这些文档到 Claude、VSCode 等，通过 MCP 获取实时答案。
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