[DOCS] Amends text with embedding_size info (#2469) (#2471)

(cherry picked from commit 1772892)

Co-authored-by: István Zoltán Szabó <[email protected]>

Author: mergify[bot]

docs/en/stack/ml/nlp/ml-nlp-text-emb-vector-search-example.asciidoc

@@ -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]
 --------------------------------------------------