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[DOCS] Amends text with embedding_size info #2469

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Jul 13, 2023
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[DOCS] Amends text with embedding_size info #2469

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baedd25
[DOCS] Amends text with embedding_size info.
szabosteve Jul 13, 2023
41fcaae
[DOCS] Fixes URL.
szabosteve Jul 13, 2023
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10 changes: 7 additions & 3 deletions docs/en/stack/ml/nlp/ml-nlp-text-emb-vector-search-example.asciidoc
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Expand Up @@ -194,9 +194,13 @@ index failures into a different index.

Before ingesting the data through the pipeline, create the mappings of the
destination index, in particular for the field `text_embedding.predicted_value`
where the ingest processor stores the embeddings. The msmarco-MiniLM-L-12-v3 model produces
embeddings with 384 dimensions; the `dense_vector` field must be configured
with the same number of dimensions as specified by the `dims` option.
where the ingest processor stores the embeddings. The `dense_vector` field must
be configured with the same number of dimensions (`dims`) as the text embedding
produced by the model. That value can be found in the `embedding_size` option in
the model configuration either under the Trained Models page in {kib} or in the
response body of the {ref}/get-trained-models.html[Get trained models API] call.
The msmarco-MiniLM-L-12-v3 model has embedding_size of 384, so `dims` is set to
384.

[source,js]
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