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typo correction, add meta, add isa requirements
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docs/index.rst

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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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.. meta::
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:description: This website introduces Intel® Extension for PyTorch*
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:keywords: Intel optimization, PyTorch, Intel® Extension for PyTorch*
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Welcome to Intel® Extension for PyTorch* Documentation
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######################################################
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docs/tutorials/features/int8.md

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The quantization functionality in Intel® Extension for PyTorch\* currently only supports post-training quantization. This tutorial introduces how the quantization works in the Intel® Extension for PyTorch\* side.
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We fully utilize Pytorch quantization components as much as possible, such as PyTorch [Observer method](https://pytorch.org/docs/1.11/quantization-support.html#torch-quantization-observer). To make a PyTorch user be able to easily use the quantization API, API for quantization in Intel® Extension for PyTorch\* is very similar to those in PyTorch. Intel® Extension for PyTorch\* quantization supports a default recipe to automatically decide which operators should be quanized or not. This brings a satisfying performance and accuracy tradeoff.
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We fully utilize Pytorch quantization components as much as possible, such as PyTorch [Observer method](https://pytorch.org/docs/1.11/quantization-support.html#torch-quantization-observer). To make a PyTorch user be able to easily use the quantization API, API for quantization in Intel® Extension for PyTorch\* is very similar to those in PyTorch. Intel® Extension for PyTorch\* quantization supports a default recipe to automatically decide which operators should be quantized or not. This brings a satisfying performance and accuracy tradeoff.
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## Static Quantization
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docs/tutorials/installation.md

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|Operating System|CentOS 7, RHEL 8, Rocky Linux 8.5, Ubuntu newer than 18.04|
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|Python|See prebuilt wheel files availability matrix below|
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* Intel® Extension for PyTorch\* is functional on systems with AVX2 instruction set support (such as Intel® Core™ Processor Family and Intel® Xeon® Processor formerly Broadwell). However, it is highly recommended to run on systems with AVX-512 and above instructions support for optimal performance (such as Intel® Xeon® Scalable Processors).
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## Install PyTorch
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Make sure PyTorch is installed so that the extension will work properly. For each PyTorch release, we have a corresponding release of the extension. Here are the PyTorch versions that we support and the mapping relationship:

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