[ML DOCS]Timeout only applies to ELSER and built in E5 models (#111159)

docs/reference/inference/put-inference.asciidoc

@@ -43,11 +43,3 @@ The following services are available through the {infer} API, click the links to
 * <<infer-service-hugging-face,Hugging Face>>
 * <<infer-service-mistral,Mistral>>
 * <<infer-service-openai,OpenAI>>
-
-[NOTE]
-====
-You might see a 502 bad gateway error in the response when using the {kib} Console.
-This error usually just reflects a timeout, while the model downloads in the background.
-You can check the download progress in the {ml-app} UI.
-If using the Python client, you can set the `timeout` parameter to a higher value.
-====

docs/reference/inference/service-elasticsearch.asciidoc

@@ -35,7 +35,7 @@ Available task types:
 
 `service`::
 (Required, string)
-The type of service supported for the specified task type. In this case, 
+The type of service supported for the specified task type. In this case,
 `elasticsearch`.
 
 `service_settings`::
@@ -58,7 +58,7 @@ The total number of allocations this model is assigned across machine learning n
 
 `num_threads`:::
 (Required, integer)
-Sets the number of threads used by each model allocation during inference. This generally increases the speed per inference request. The inference process is a compute-bound process; `threads_per_allocations` must not exceed the number of available allocated processors per node. 
+Sets the number of threads used by each model allocation during inference. This generally increases the speed per inference request. The inference process is a compute-bound process; `threads_per_allocations` must not exceed the number of available allocated processors per node.
 Must be a power of 2. Max allowed value is 32.
 
 `task_settings`::
@@ -98,6 +98,14 @@ PUT _inference/text_embedding/my-e5-model
 Valid values are `.multilingual-e5-small` and `.multilingual-e5-small_linux-x86_64`.
 For further details, refer to the {ml-docs}/ml-nlp-e5.html[E5 model documentation].
 
+[NOTE]
+====
+You might see a 502 bad gateway error in the response when using the {kib} Console.
+This error usually just reflects a timeout, while the model downloads in the background.
+You can check the download progress in the {ml-app} UI.
+If using the Python client, you can set the `timeout` parameter to a higher value.
+====
+
 [discrete]
 [[inference-example-eland]]
 ==== Models uploaded by Eland via the elasticsearch service
@@ -119,4 +127,4 @@ PUT _inference/text_embedding/my-msmarco-minilm-model
 ------------------------------------------------------------
 // TEST[skip:TBD]
 <1> The `model_id` must be the ID of a text embedding model which has already been
-{ml-docs}/ml-nlp-import-model.html#ml-nlp-import-script[uploaded through Eland].
+{ml-docs}/ml-nlp-import-model.html#ml-nlp-import-script[uploaded through Eland].

docs/reference/inference/service-elser.asciidoc

@@ -34,7 +34,7 @@ Available task types:
 
 `service`::
 (Required, string)
-The type of service supported for the specified task type. In this case, 
+The type of service supported for the specified task type. In this case,
 `elser`.
 
 `service_settings`::
@@ -51,7 +51,7 @@ The total number of allocations this model is assigned across machine learning n
 
 `num_threads`:::
 (Required, integer)
-Sets the number of threads used by each model allocation during inference. This generally increases the speed per inference request. The inference process is a compute-bound process; `threads_per_allocations` must not exceed the number of available allocated processors per node. 
+Sets the number of threads used by each model allocation during inference. This generally increases the speed per inference request. The inference process is a compute-bound process; `threads_per_allocations` must not exceed the number of available allocated processors per node.
 Must be a power of 2. Max allowed value is 32.
 
 
@@ -92,4 +92,12 @@ Example response:
   "task_settings": {}
 }
 ------------------------------------------------------------
-// NOTCONSOLE
+// NOTCONSOLE
+
+[NOTE]
+====
+You might see a 502 bad gateway error in the response when using the {kib} Console.
+This error usually just reflects a timeout, while the model downloads in the background.
+You can check the download progress in the {ml-app} UI.
+If using the Python client, you can set the `timeout` parameter to a higher value.
+====