diff --git a/docs/readthedocs/source/doc/LLM/Overview/install_gpu.md b/docs/readthedocs/source/doc/LLM/Overview/install_gpu.md index d6cc43bb..89457cad 100644 --- a/docs/readthedocs/source/doc/LLM/Overview/install_gpu.md +++ b/docs/readthedocs/source/doc/LLM/Overview/install_gpu.md @@ -18,9 +18,28 @@ To apply Intel GPU acceleration, there're several prerequisite steps for tools i * Step 2: Install or update to latest [GPU driver](https://www.intel.com/content/www/us/en/download/785597/intel-arc-iris-xe-graphics-windows.html) -* Step 3: Install Intel® oneAPI Base Toolkit 2024.0: download and install [Intel® oneAPI Base Toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html?operatingsystem=window&distributions=offline>) version 2024.0 through Offline Installer. - - During installation, you could just continue with "Recommended Installation". If you would like to continue with "Custom Installation", please note that oneAPI Deep Neural Network Library, oneAPI Math Kernel Library, and oneAPI DPC++/C++ Compiler are required, the other components are optional. +* Step 3 (Recommended): Install [Miniconda](https://docs.anaconda.com/free/miniconda/) for Python environment management. Choose **Miniconda installer for Windows**. + +* Step 4: Install Intel® oneAPI Base Toolkit 2024.0: + + First, Create a Python 3.9 enviroment and activate it. In Anaconda Prompt: + + ```cmd + conda create -n llm python=3.9 libuv + + conda activate llm + ``` + + ```eval_rst + .. important:: + + ``ipex-llm`` is tested with Python 3.9, 3.10 and 3.11. Python 3.9 is recommended for best practices. + ``` + + Then, use `pip` to install the **Intel oneAPI Base Toolkit 2024.0**: + ```cmd + pip install dpcpp-cpp-rt==2024.0.2 mkl-dpcpp==2024.0.0 onednn==2024.0.0 + ``` -### Install IPEX-LLM From PyPI - -We recommend using [miniconda](https://docs.conda.io/en/latest/miniconda.html) to create a python 3.9 enviroment: - -```eval_rst -.. important:: - - ``ipex-llm`` is tested with Python 3.9, 3.10 and 3.11. Python 3.9 is recommended for best practices. -``` +### Install IPEX-LLM +#### Install IPEX-LLM From PyPI The easiest ways to install `ipex-llm` is the following commands, choosing either US or CN website for `extra-index-url`: @@ -76,7 +88,7 @@ choosing either US or CN website for `extra-index-url`: pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/cn/ ``` -### Install IPEX-LLM From Wheel +#### Install IPEX-LLM From Wheel If you encounter network issues when installing IPEX, you can also install IPEX-LLM dependencies for Intel XPU from source archives. First you need to download and install torch/torchvision/ipex from wheels listed below before installing `ipex-llm`. @@ -106,17 +118,15 @@ pip install --pre --upgrade ipex-llm[xpu] ### Runtime Configuration -To use GPU acceleration on Windows, several environment variables are required before running a GPU example. +To use GPU acceleration on Windows, several environment variables are required before running a GPU example: - - -Make sure you are using CMD (Anaconda Prompt if using conda) as PowerShell is not supported, and configure oneAPI environment variables with: + ```eval_rst .. tabs:: @@ -162,11 +172,6 @@ If you met error when importing `intel_extension_for_pytorch`, please ensure tha ```cmd conda install libuv ``` -* Make sure you have configured oneAPI environment variables in your Anaconda Prompt through - ```cmd - call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" - ``` - Please note that you need to set these environment variables again once you have a new Anaconda Prompt window. - - -Download and install the [**Intel oneAPI Base Toolkit 2024.0**](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html?operatingsystem=window&distributions=offline). During installation, you can continue with the default installation settings. + -### Setup Python Environment +### Install Miniconda Visit [Miniconda installation page](https://docs.anaconda.com/free/miniconda/), download the **Miniconda installer for Windows**, and follow the instructions to complete the installation. @@ -57,14 +52,19 @@ Visit [Miniconda installation page](https://docs.anaconda.com/free/miniconda/), -After installation, open the **Anaconda Prompt**, create a new python environment `llm`: + +### Install oneAPI + +Open the **Anaconda Prompt**. Then create a new python environment `llm` and activate it: ```cmd conda create -n llm python=3.9 libuv -``` -Activate the newly created environment `llm`: -```cmd conda activate llm ``` + +Use `pip` to install the **Intel oneAPI Base Toolkit 2024.0**: +```cmd +pip install dpcpp-cpp-rt==2024.0.2 mkl-dpcpp==2024.0.0 onednn==2024.0.0 +``` ## Install `ipex-llm` @@ -96,14 +96,14 @@ Choose either US or CN website for `extra-index-url`: You can verify if `ipex-llm` is successfully installed following below steps. ### Step 1: Runtime Configurations - * Open the **Anaconda Prompt** and activate the Python environment `llm` you previously created: +* Open the **Anaconda Prompt** and activate the Python environment `llm` you previously created: ```cmd conda activate llm ``` - * Configure oneAPI variables by running the following command: + * Set the following environment variables according to your device: ```eval_rst diff --git a/docs/readthedocs/source/doc/LLM/Quickstart/llama_cpp_quickstart.md b/docs/readthedocs/source/doc/LLM/Quickstart/llama_cpp_quickstart.md index 092ac85e..82222dc1 100644 --- a/docs/readthedocs/source/doc/LLM/Quickstart/llama_cpp_quickstart.md +++ b/docs/readthedocs/source/doc/LLM/Quickstart/llama_cpp_quickstart.md @@ -17,7 +17,7 @@ For Linux system, we recommend Ubuntu 20.04 or later (Ubuntu 22.04 is preferred) Visit the [Install IPEX-LLM on Linux with Intel GPU](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html), follow [Install Intel GPU Driver](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html#install-intel-gpu-driver) and [Install oneAPI](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html#install-oneapi) to install GPU driver and [Intel® oneAPI Base Toolkit 2024.0](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html). ### Windows -Visit the [Install IPEX-LLM on Windows with Intel GPU Guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_windows_gpu.html), and follow [Install Prerequisites](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_windows_gpu.html#install-prerequisites) to install [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) Community Edition, latest [GPU driver](https://www.intel.com/content/www/us/en/download/785597/intel-arc-iris-xe-graphics-windows.html) and [Intel® oneAPI Base Toolkit 2024.0](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html). +Visit the [Install IPEX-LLM on Windows with Intel GPU Guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_windows_gpu.html), and follow [Install Prerequisites](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_windows_gpu.html#install-prerequisites) to install [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) Community Edition, latest [GPU driver](https://www.intel.com/content/www/us/en/download/785597/intel-arc-iris-xe-graphics-windows.html) and Intel® oneAPI Base Toolkit 2024.0. ## 1 Install IPEX-LLM for llama.cpp