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<3> The name of the embedding model to use. You can find the list of Cohere
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embedding models https://docs.cohere.com/reference/embed[here].
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+ NOTE: When using this model the recommended similarity measure to use in the
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+ `dense_vector` field mapping is `dot_product` . In the case of Cohere models, the
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+ embeddings are normalized to unit length in which case the `dot_product` and
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+ the `cosine` measures are equivalent.
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// end::cohere[]
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@@ -35,8 +42,6 @@ PUT _inference/text_embedding/openai_embeddings <1>
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"service_settings": {
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"api_key": "<api_key>", <2>
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"model_id": "text-embedding-ada-002" <3>
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- },
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- "task_settings": {
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}
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}
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------------------------------------------------------------
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embedding models
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https://platform.openai.com/docs/guides/embeddings/embedding-models[here].
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+ NOTE: When using this model the recommended similarity measure to use in the
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+ `dense_vector` field mapping is `dot_product` . In the case of OpenAI models, the
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+ embeddings are normalized to unit length in which case the `dot_product` and
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+ the `cosine` measures are equivalent.
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+
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// end::openai[]
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