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* Add Using ROCm for AI:wq Add PyTorch Docker installation images Split doc into subtopics Add metadata Clean up index Clean up hugging face guide Clean up installation guide Fix rST formatting Clean up install and train-a-model Clean up MAD Delete unused file Add ref anchors and clean up MAD doc Add formatting fixes Update toc and section index Format some code blocks Remove install guide and update toc Chop installation guide Clean up deployment and hugging face sections Change headings to end in -ing Fix spelling in Training a model Delete MAD and split out install content Fix formatting Change words to satisfy spellcheck linter * Add review suggestions and add helpful links Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> Add helpful links and add review suggestions Remove fine-tuning link and links to D5 and MAGMA Update docs/how-to/rocm-for-ai/deploy-your-model.rst Co-authored-by: Young Hui - AMD <145490163+yhuiYH@users.noreply.github.com> Update DeepSpeed link Add subheading to ML framework installation and closing blurb to hugging face models guide * Reorder topics
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.. meta::
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:description: How to use ROCm for AI
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:keywords: ROCm, AI, LLM, train, fine-tune, FSDP, DeepSpeed, LLaMA, tutorial
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.. _rocm-for-ai-install:
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***********************************************
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Installing ROCm and machine learning frameworks
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***********************************************
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Before getting started, install ROCm and supported machine learning frameworks.
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.. grid:: 1
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.. grid-item-card:: Pre-install
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Each release of ROCm supports specific hardware and software configurations. Before installing, consult the
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:doc:`System requirements <rocm-install-on-linux:reference/system-requirements>` and
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:doc:`Installation prerequisites <rocm-install-on-linux:how-to/prerequisites>` guides.
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If you’re new to ROCm, refer to the :doc:`ROCm quick start install guide for Linux
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<rocm-install-on-linux:tutorial/quick-start>`.
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If you’re using a Radeon GPU for graphics-accelerated applications, refer to the
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:doc:`Radeon installation instructions <radeon:docs/install/install-radeon>`.
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ROCm supports two methods for installation. There is no difference in the final ROCm installation between these two
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methods. You can also opt for :ref:`single-version or multi-version installation
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<rocm-install-on-linux:installation-types>`.
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* :doc:`Using your Linux distribution's package manager <rocm-install-on-linux:how-to/native-install/index>`
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* :doc:`Using the AMDGPU installer <rocm-install-on-linux:how-to/amdgpu-install>`
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.. grid:: 1
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.. grid-item-card:: Post-install
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Follow the :doc:`post-installation instructions <rocm-install-on-linux:how-to/native-install/post-install>` to
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configure your system linker, PATH, and verify the installation.
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If you encounter any issues during installation, refer to the
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:doc:`Installation troubleshooting <rocm-install-on-linux:how-to/native-install/install-faq>` guide.
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Machine learning frameworks
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===========================
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ROCm supports popular machine learning frameworks and libraries including `PyTorch
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<https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package>`_, `TensorFlow
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<https://tensorflow.org>`_, `JAX <https://jax.readthedocs.io/en/latest>`_, and `DeepSpeed
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<https://cloudblogs.microsoft.com/opensource/2022/03/21/supporting-efficient-large-model-training-on-amd-instinct-gpus-with-deepspeed/>`_.
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Review the framework installation documentation. For ease-of-use, it's recommended to use official ROCm prebuilt Docker
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images with the framework pre-installed.
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* :doc:`PyTorch for ROCm <rocm-install-on-linux:how-to/3rd-party/pytorch-install>`
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* :doc:`TensorFlow for ROCm <rocm-install-on-linux:how-to/3rd-party/tensorflow-install>`
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* :doc:`JAX for ROCm <rocm-install-on-linux:how-to/3rd-party/jax-install>`
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The sections that follow in :doc:`Training a model <train-a-model>` are geared for a ROCm with PyTorch installation.
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