From 00f007cbb13fd6ce6b94a3366970f1b18a9aaa27 Mon Sep 17 00:00:00 2001 From: Mohan Gandhi Date: Thu, 18 Aug 2022 12:21:29 -0700 Subject: [PATCH] Update the studio kernal notebook to TF 2.6 (#3568) Changed the studio notebook TF 2.6 Verified the changes by local testing --- sagemaker-inference-recommender/inference-recommender.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sagemaker-inference-recommender/inference-recommender.ipynb b/sagemaker-inference-recommender/inference-recommender.ipynb index bbbbf958fd..95eb54c7e8 100644 --- a/sagemaker-inference-recommender/inference-recommender.ipynb +++ b/sagemaker-inference-recommender/inference-recommender.ipynb @@ -24,7 +24,7 @@ "source": [ "## 2. Setup \n", "\n", - "Note that we are using the `conda_tensorflow2_p36` kernel in SageMaker Notebook Instances. This is running Python 3.6 and TensorFlow 2.1.3. If you'd like to use the same setup, in the AWS Management Console, go to the Amazon SageMaker console. Choose Notebook Instances, and click create a new notebook instance. Upload the current notebook and set the kernel. You can also run this in SageMaker Studio Notebooks with the `TensorFlow 2.1 Python 3.6 CPU Optimized` kernel.\n", + "Note that we are using the `conda_tensorflow2_p36` kernel in SageMaker Notebook Instances. This is running Python 3.6 and TensorFlow 2.1.3. If you'd like to use the same setup, in the AWS Management Console, go to the Amazon SageMaker console. Choose Notebook Instances, and click create a new notebook instance. Upload the current notebook and set the kernel. You can also run this in SageMaker Studio Notebooks with the `TensorFlow 2.6 Python 3.8 CPU Optimized` kernel.\n", "\n", "In the next steps, you'll import standard methods and libraries as well as set variables that will be used in this notebook. The `get_execution_role` function retrieves the AWS Identity and Access Management (IAM) role you created at the time of creating your notebook instance." ]