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improve intro page
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doc/api/training/smd_model_parallel.rst

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@@ -11,10 +11,11 @@ across multiple GPUs with minimal code changes. The library's API can be accesse
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.. tip::
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We recommended using this API documentation with the conceptual guide at
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We recommend that you use this API documentation along with the conceptual guide at
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`SageMaker's Distributed Model Parallel
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<http://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel.html>`_
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in the *Amazon SageMaker developer guide*. This developer guide documentation includes:
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in the *Amazon SageMaker developer guide*.
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The conceptual guide includes the following topics:
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- An overview of model parallelism, and the library's
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`core features <https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel-core-features.html>`_,
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.. important::
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The model parallel library only supports training jobs using CUDA 11. When you define a PyTorch or TensorFlow
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``Estimator`` with ``modelparallel`` parameter ``enabled`` set to ``True``,
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it uses CUDA 11. When you extend or customize your own training image
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you must use a CUDA 11 base image. See
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`Extend or Adapt A Docker Container that Contains the Model Parallel Library
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<https://integ-docs-aws.amazon.com/sagemaker/latest/dg/model-parallel-use-api.html#model-parallel-customize-container>`__
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for more information.
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The model parallel library only supports SageMaker training jobs using CUDA 11.
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Make sure you use the pre-built Deep Learning Containers, or use the right CUDA version
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if you use a custom training container.
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.. tip::
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If you want to extend or customize your own training image
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you must use a CUDA 11 base image. For more information, see `Extend a Prebuilt Docker
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Container that Contains SageMaker's Distributed Model Parallel Library
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<https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel-sm-sdk.html#model-parallel-customize-container>`_
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and `Create Your Own Docker Container with the SageMaker Distributed Model Parallel Library
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<https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel-sm-sdk.html#model-parallel-bring-your-own-container>`_.

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