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"Embeddings typically represent text as a \"dense\" vector such that texts with similar meanings are gemoetrically close. This lets us retrieve relevant information just by passing in a question, without knowledge of any specific key-terms used in the document.\n",
"Embeddings typically represent text as a \"dense\" vector such that texts with similar meanings are geometrically close. This lets us retrieve relevant information just by passing in a question, without knowledge of any specific key-terms used in the document.\n",
"\n",
"Return documents based on similarity to a string query:"