embed score.py instead of just linking it

Author: shohei1029

articles/machine-learning/how-to-deploy-online-endpoints.md

@@ -375,18 +375,18 @@ For supported general-purpose and GPU instance types, see [Managed online endpoi
 
 ### Use more than one model
 
-Currently, you can specify only one model per deployment in the YAML. If you've more than one model, when you register the model, copy all the models as files or subdirectories into a folder that you use for registration. In your scoring script, use the environment variable `AZUREML_MODEL_DIR` to get the path to the model root folder. The underlying directory structure is retained. For an example of deploying multiple models to one deployment, see [Deploy multiple models to one deployment](https://github.com/Azure/azureml-examples/blob/main/cli/endpoints/online/custom-container/minimal/multimodel/README.md).
+Currently, you can specify only one model per deployment in the YAML. If you've more than one model, when you register the model, copy all the models as files or subdirectories into a folder that you use for registration. In your scoring script, use the environment variable `AZUREML_MODEL_DIR` to get the path to the model root folder. The underlying directory structure is retained. For an example of deploying multiple models to one deployment, see [Deploy multiple models to one deployment](https://github.com/Azure/azureml-examples/blob/main/cli/endpoints/online/custom-container/minimal/multimodel).
 
 ## Understand the scoring script
 
 > [!TIP]
 > The format of the scoring script for online endpoints is the same format that's used in the preceding version of the CLI and in the Python SDK.
 
 # [Azure CLI](#tab/azure-cli)
-As noted earlier, the script specified in `code_configuration.scoring_script` must have an `init()` function and a `run()` function. This example uses the [score.py file](https://github.com/Azure/azureml-examples/blob/main/cli/endpoints/online/model-1/onlinescoring/score.py). 
+As noted earlier, the script specified in `code_configuration.scoring_script` must have an `init()` function and a `run()` function. 
 
 # [Python](#tab/python)
-As noted earlier, the script specified in `CodeConfiguration(scoring_script="score.py")` must have an `init()` function and a `run()` function. This example uses the [score.py file](https://github.com/Azure/azureml-examples/blob/main/sdk/python/endpoints/online/model-1/onlinescoring/score.py). 
+As noted earlier, the script specified in `CodeConfiguration(scoring_script="score.py")` must have an `init()` function and a `run()` function. 
 
 # [ARM template](#tab/arm)
 
@@ -404,6 +404,10 @@ When using a template for deployment, you must first upload the scoring file(s)
 
 ---
 
+This example uses the [score.py file](https://github.com/Azure/azureml-examples/blob/main/sdk/python/endpoints/online/model-1/onlinescoring/score.py):
+__score.py__
+:::code language="python" source="~/azureml-examples-main/cli/endpoints/online/model-1/onlinescoring/score.py" :::
+
 The `init()` function is called when the container is initialized or started. Initialization typically occurs shortly after the deployment is created or updated. Write logic here for global initialization operations like caching the model in memory (as we do in this example). The `run()` function is called for every invocation of the endpoint and should do the actual scoring and prediction. In the example, we extract the data from the JSON input, call the scikit-learn model's `predict()` method, and then return the result.
 
 ## Deploy and debug locally by using local endpoints