Relocates applies to tags.

Author: szabosteve

explore-analyze/elastic-inference/eis.md

@@ -15,7 +15,7 @@ Instead, you can use {{ml}} models for ingest, search, and chat independently of
 
 * Your Elastic deployment or project comes with a default [`Elastic Managed LLM` connector](https://www.elastic.co/docs/reference/kibana/connectors-kibana/elastic-managed-llm). This connector is used in the AI Assistant, Attack Discovery, Automatic Import and Search Playground.
 
-* {applies_to}`stack: preview 9.1` {applies_to}`serverless: preview` You can use [ELSER](/explore-analyze/machine-learning/nlp/ml-nlp-elser.md) to perform semantic search as a service (ELSER on EIS).
+* You can use [ELSER](/explore-analyze/machine-learning/nlp/ml-nlp-elser.md) to perform semantic search as a service (ELSER on EIS). {applies_to}`stack: preview 9.1` {applies_to}`serverless: preview`
 
 ## Region and hosting [eis-regions]
 
@@ -26,7 +26,10 @@ ELSER requests are managed by Elastic's own EIS infrastructure.
 
 ## ELSER via Elastic {{infer-cap}} Service (ELSER on EIS)
 
-{applies_to}`stack: preview 9.1` {applies_to}`serverless: preview`
+```{applies_to}
+stack: preview 9.1
+serverless: preview
+```
 
 ELSER on EIS enables you to use the ELSER model without using ML nodes in your infrastructure and with that, it simplifies the semantic search and hybrid search experience.
 

explore-analyze/elastic-inference/inference-api.md

@@ -30,7 +30,7 @@ The following section lists the default {{infer}} endpoints, identified by their
 
 ### Default endpoints for Elastic {{infer-cap}} Service (EIS)
 
-- {applies_to}`stack: preview 9.1` {applies_to}`serverless: preview` `.elser-2-elastic`: uses the [ELSER](/explore-analyze/machine-learning/nlp/ml-nlp-elser.md) trained model as an Elastic {{infer-cap}} Service for `sparse_embedding` tasks (recommended for English language text). The `model_id` is `.elser_model_2`.
+- `.elser-2-elastic`: uses the [ELSER](/explore-analyze/machine-learning/nlp/ml-nlp-elser.md) trained model as an Elastic {{infer-cap}} Service for `sparse_embedding` tasks (recommended for English language text). The `model_id` is `.elser_model_2`. {applies_to}`stack: preview 9.1` {applies_to}`serverless: preview`
 
 ### Default endpoints used on ML-nodes