diff --git a/notebooks/integrations/cohere/inference-cohere.ipynb b/notebooks/integrations/cohere/inference-cohere.ipynb
index 3064452d..b8888c23 100644
--- a/notebooks/integrations/cohere/inference-cohere.ipynb
+++ b/notebooks/integrations/cohere/inference-cohere.ipynb
@@ -184,9 +184,9 @@
     "id": "96788aa1"
    },
    "source": [
-    "## Create the inference task\n",
+    "## Create the inference endpoint\n",
     "\n",
-    "Let's create the inference task by using the [Create inference API](https://www.elastic.co/guide/en/elasticsearch/reference/current/put-inference-api.html).\n",
+    "Let's create the inference endpoint by using the [Create inference API](https://www.elastic.co/guide/en/elasticsearch/reference/current/put-inference-api.html).\n",
     "\n",
     "You'll need an Cohere API key for this that you can find in your Cohere account under the [API keys section](https://dashboard.cohere.com/api-keys). A paid membership is required to complete the steps in this notebook as the Cohere free trial API usage is limited."
    ]
@@ -204,7 +204,7 @@
     "\n",
     "client.inference.put_model(\n",
     "    task_type=\"text_embedding\",\n",
-    "    model_id=\"cohere_embeddings\",\n",
+    "    inference_id=\"cohere_embeddings\",\n",
     "    body={\n",
     "        \"service\": \"cohere\",\n",
     "        \"service_settings\": {\n",
@@ -226,7 +226,7 @@
    "source": [
     "## Create an ingest pipeline with an inference processor\n",
     "\n",
-    "Create an ingest pipeline with an inference processor by using the [`put_pipeline`](https://www.elastic.co/guide/en/elasticsearch/reference/master/put-pipeline-api.html) method. Reference the Cohere model created above to infer against the data that is being ingested in the pipeline."
+    "Create an ingest pipeline with an inference processor by using the [`put_pipeline`](https://www.elastic.co/guide/en/elasticsearch/reference/master/put-pipeline-api.html) method. Reference the inference endpoint created above as the `model_id` to infer against the data that is being ingested in the pipeline."
    ]
   },
   {
@@ -265,7 +265,7 @@
     "Let's note a few important parameters from that API call:\n",
     "\n",
     "- `inference`: A processor that performs inference using a machine learning model.\n",
-    "- `model_id`: Specifies the ID of the machine learning model to be used. In this example, the model ID is set to `cohere_embeddings`.\n",
+    "- `model_id`: Specifies the ID of the inference endpoint to be used. In this example, the model ID is set to `cohere_embeddings`.\n",
     "- `input_output`: Specifies input and output fields.\n",
     "- `input_field`: Field name from which the `dense_vector` representation is created.\n",
     "- `output_field`:  Field name which contains inference results."
@@ -406,7 +406,7 @@
     "        \"field\": \"plot_embedding\",\n",
     "        \"query_vector_builder\": {\n",
     "            \"text_embedding\": {\n",
-    "                \"model_id\": \"cohere_embeddings\",\n",
+    "                \"inference_id\": \"cohere_embeddings\",\n",
     "                \"model_text\": \"Fighting movie\",\n",
     "            }\n",
     "        },\n",
diff --git a/notebooks/search/07-inference.ipynb b/notebooks/search/07-inference.ipynb
index e0a53a7b..bc443d29 100644
--- a/notebooks/search/07-inference.ipynb
+++ b/notebooks/search/07-inference.ipynb
@@ -154,9 +154,9 @@
    "id": "840d92f0",
    "metadata": {},
    "source": [
-    "## Create the inference task\n",
+    "## Create the inference endpoint\n",
     "\n",
-    "Let's create the inference task by using the [Create inference API](https://www.elastic.co/guide/en/elasticsearch/reference/current/put-inference-api.html).\n",
+    "Let's create the inference endpoint by using the [Create inference API](https://www.elastic.co/guide/en/elasticsearch/reference/current/put-inference-api.html).\n",
     "\n",
     "You'll need an OpenAI API key for this that you can find in your OpenAI account under the [API keys section](https://platform.openai.com/api-keys). A paid membership is required to complete the steps in this notebook as the OpenAI free trial API usage is limited."
    ]
@@ -172,7 +172,7 @@
     "\n",
     "client.inference.put_model(\n",
     "    task_type=\"text_embedding\",\n",
-    "    model_id=\"my_openai_embedding_model\",\n",
+    "    inference_id=\"my_openai_embedding_model\",\n",
     "    body={\n",
     "        \"service\": \"openai\",\n",
     "        \"service_settings\": {\"api_key\": API_KEY},\n",
@@ -181,6 +181,14 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "1f2e48b7",
+   "metadata": {},
+   "source": [
+    "**NOTE:** If you use Elasticsearch 8.12, you must change `inference_id` in the snippet above to `model_id`! "
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "1024d070",
@@ -188,7 +196,7 @@
    "source": [
     "## Create an ingest pipeline with an inference processor\n",
     "\n",
-    "Create an ingest pipeline with an inference processor by using the [`put_pipeline`](https://www.elastic.co/guide/en/elasticsearch/reference/master/put-pipeline-api.html) method. Reference the OpenAI model created above to infer against the data that is being ingested in the pipeline."
+    "Create an ingest pipeline with an inference processor by using the [`put_pipeline`](https://www.elastic.co/guide/en/elasticsearch/reference/master/put-pipeline-api.html) method. Reference the inference endpoint created above as `model_id` to infer against the data that is being ingested in the pipeline."
    ]
   },
   {
@@ -223,7 +231,7 @@
     "Let's note a few important parameters from that API call:\n",
     "\n",
     "- `inference`: A processor that performs inference using a machine learning model.\n",
-    "- `model_id`: Specifies the ID of the machine learning model to be used. In this example, the model ID is set to `my_openai_embedding_model`. Use the model ID you defined when created the inference task.\n",
+    "- `model_id`: Specifies the ID of the inference endpoint to be used. In this example, the inference ID is set to `my_openai_embedding_model`. Use the inference ID you defined when created the inference task.\n",
     "- `input_output`: Specifies input and output fields.\n",
     "- `input_field`: Field name from which the `dense_vector` representation is created.\n",
     "- `output_field`:  Field name which contains inference results. "
@@ -348,7 +356,7 @@
     "        \"field\": \"plot_embedding\",\n",
     "        \"query_vector_builder\": {\n",
     "            \"text_embedding\": {\n",
-    "                \"model_id\": \"my_openai_embedding_model\",\n",
+    "                \"inference_id\": \"my_openai_embedding_model\",\n",
     "                \"model_text\": \"Fighting movie\",\n",
     "            }\n",
     "        },\n",
@@ -364,6 +372,20 @@
     "    plot = hit[\"_source\"][\"plot\"]\n",
     "    print(f\"Score: {score}\\nTitle: {title}\\nPlot: {plot}\\n\")"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7e4055ba",
+   "metadata": {},
+   "source": [
+    "**NOTE:** If you use Elasticsearch 8.12, you must change `inference_id` in the snippet above to `model_id`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "59220b82",
+   "metadata": {},
+   "source": []
   }
  ],
  "metadata": {