OLS-1790: minor edit

Author: rh-tokeefe

modules/ols-large-language-model-requirements.adoc

@@ -43,16 +43,16 @@ To use {azure-official} with {ols-official}, you need access to link:https://azu
 
 You can configure {rhelai} as the (Large Language Model) LLM provider. 
 
-{ols-long} version 1.0 supports vLLM Server version 0.8.4. When self-hosting a large language model with {rhelai}, you can use vLLM Server as the inference engine for your model deployment.
-
 Because the {rhel} is in a different environment than the {ols-long} deployment, the model deployment must allow access using a secure connection. For more information, see link:https://docs.redhat.com/en/documentation/red_hat_enterprise_linux_ai/1.2/html-single/building_your_rhel_ai_environment/index#creating_secure_endpoint[Optional: Allowing access to a model from a secure endpoint].
 
+{ols-long} version 1.0 supports vLLM Server version 0.8.4. When self-hosting a large language model with {rhelai}, you can use vLLM Server as the inference engine for your model deployment.
+
 
 [id="rhoai_{context}"]
 == {rhoai}
 
 {rhoai} is OpenAI API-compatible, and is configured largely the same as the OpenAI provider. 
 
-{ols-long} version 1.0 supports vLLM Server version 0.8.4. When self-hosting a large language model with {rhoai}, you can use vLLM Server as the inference engine for your model deployment.
+You need a Large Language Model (LLM) deployed on the single model-serving platform of {rhoai} using the Virtual Large Language Model (vLLM) runtime. If the model deployment is in a different {ocp-short-name} environment than the {ols-long} deployment, the model deployment must include a route to expose it outside the cluster. For more information, see link:https://docs.redhat.com/en/documentation/red_hat_openshift_ai_self-managed/2-latest/html/serving_models/serving-large-models_serving-large-models#about-the-single-model-serving-platform_serving-large-models[About the single-model serving platform].
 
-You need a Large Language Model (LLM) deployed on the single model-serving platform of {rhoai} using the Virtual Large Language Model (vLLM) runtime. If the model deployment is in a different {ocp-short-name} environment than the {ols-long} deployment, the model deployment must include a route to expose it outside the cluster. For more information, see link:https://docs.redhat.com/en/documentation/red_hat_openshift_ai_self-managed/2-latest/html/serving_models/serving-large-models_serving-large-models#about-the-single-model-serving-platform_serving-large-models[About the single-model serving platform].
+{ols-long} version 1.0 supports vLLM Server version 0.8.4. When self-hosting a large language model with {rhoai}, you can use vLLM Server as the inference engine for your model deployment.