[DOCS] Link to Elastic Rerank model landing page

docs/reference/inference/service-elasticsearch.asciidoc

@@ -153,7 +153,7 @@ For further details, refer to the {ml-docs}/ml-nlp-elser.html[ELSER model docume
 [[inference-example-elastic-reranker]]
 ==== Elastic Rerank via the `elasticsearch` service
 
-The following example shows how to create an {infer} endpoint called `my-elastic-rerank` to perform a `rerank` task type using the built-in Elastic Rerank cross-encoder model.
+The following example shows how to create an {infer} endpoint called `my-elastic-rerank` to perform a `rerank` task type using the built-in {ml-docs}/ml-nlp-rerank.html[Elastic Rerank] cross-encoder model.
 
 The API request below will automatically download the Elastic Rerank model if it isn't already downloaded and then deploy the model.
 Once deployed, the model can be used for semantic re-ranking with a <<text-similarity-reranker-retriever-example-elastic-rerank,`text_similarity_reranker` retriever>>.

docs/reference/search/retriever.asciidoc

@@ -442,7 +442,7 @@ If the child retriever already specifies any filters, then this top-level filter
 [[text-similarity-reranker-retriever-example-elastic-rerank]]
 ==== Example: Elastic Rerank
 
-This examples demonstrates how to deploy the Elastic Rerank model and use it to re-rank search results using the `text_similarity_reranker` retriever.
+This example demonstrates how to deploy the {ml-docs}/ml-nlp-rerank.html[Elastic Rerank] model and use it to re-rank search results using the `text_similarity_reranker` retriever.
 
 Follow these steps: