Fix in image generation block

Author: liakaz

articles/machine-learning/how-to-troubleshoot-deployment.md

@@ -260,7 +260,7 @@ For more information on setting `autoscale_target_utilization`, `autoscale_max_r
 In some cases, you may need to interactively debug the Python code contained in your model deployment. For example, if the entry script is failing and the reason cannot be determined by additional logging. By using Visual Studio Code and the Python Tools for Visual Studio (PTVSD), you can attach to the code running inside the Docker container.
 
 > [!IMPORTANT]
-> This method of debugging does not work when using `Model.deploy()` and `LocalWebservice.deploy_configuration` to deploy a model locally. Instead, you must create an image using the [ContainerImage](https://docs.microsoft.com/python/api/azureml-core/azureml.core.image.containerimage?view=azure-ml-py) class. 
+> This method of debugging does not work when using `Model.deploy()` and `LocalWebservice.deploy_configuration` to deploy a model locally. Instead, you must create an image using the [Model.package()](https://docs.microsoft.com/python/api/azureml-core/azureml.core.model.model?view=azure-ml-py#package-workspace--models--inference-config-none--generate-dockerfile-false-) method.
 
 Local web service deployments require a working Docker installation on your local system. For more information on using Docker, see the [Docker Documentation](https://docs.docker.com/).