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Windows Installation

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🚧 Cortex.cpp is currently under development. Our documentation outlines the intended behavior of Cortex, which may not yet be fully implemented in the codebase.

Overview​

For Windows, Cortex.cpp can be installed in two ways:

Windows​

Install Cortex.cpp​

Cortex.cpp offers two installer types:

  • Network Installers download a minimal system and require an internet connection to fetch packages during installation.
  • Local Installers include all necessary packages, enabling offline installation without internet access.
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Before installation, make sure that you have met the required dependencies and hardware to run Cortex.

Data Folder​

By default, Cortex.cpp is installed in the following directory:


# Binary Location
C:\Users\<username>\AppData\Local\cortexcpp
# Application Data (Engines, Models and Logs folders)
C:\Users\<username>\.cortexcpp

Uninstall Cortex.cpp​

To uninstall Cortex.cpp:

  1. Navigate to Add or Remove program.
  2. Search for Cortex.cpp and click Uninstall.

Windows Subsystem Linux​

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Windows Subsystem Linux allows running Linux tools and workflows seamlessly alongside Windows applications. For more information, please see this article.

Install Cortex.cpp​

Cortex.cpp offers two installer types:

  • Network Installers download a minimal system and require an internet connection to fetch packages during installation.
  • Local Installers include all necessary packages, enabling offline installation without internet access.
info

Before installation, make sure that you have met the required dependencies and hardware to run Cortex.

  1. Download the Windows installer:
  2. Ensure that Cortex.cpp is sucessfulyy installed:

# Stable
cortex.exe
# Beta
cortex-beta.exe
# Nightly
cortex-nightly.exe

Data Folder​

By default, Cortex.cpp is installed in the following directory:


# Binary Location
C:\Users\<username>\AppData\Local\cortexcpp\cortex<env>.exe
# Application Data (Engines, Models and Logs folders)
C:\Users\<username>\.cortexcpp<env>

Uninstall Cortex.cpp​

Run the uninstaller script:


# Stable version
sudo apt remove cortexcpp
# Beta version
sudo apt remove cortexcpp-beta
# Nightly version
sudo apt remove cortexcpp-nightly

Build from Source​

  1. Clone the Cortex.cpp repository here.
  2. Navigate to the engine > vcpkg folder.
  3. Configure the vpkg:

cd vcpkg
## Windows
./bootstrap-vcpkg.bat
## WSL
./bootstrap-vcpkg.sh
vcpkg install

  1. Build the Cortex.cpp inside the build folder:

mkdir build
cd build
## Windows
cmake .. -DBUILD_SHARED_LIBS=OFF -DCMAKE_TOOLCHAIN_FILE=path_to_vcpkg_folder/vcpkg/scripts/buildsystems/vcpkg.cmake -DVCPKG_TARGET_TRIPLET=x64-windows-static
## WSL
cmake .. -DCMAKE_TOOLCHAIN_FILE=path_to_vcpkg_folder/vcpkg/scripts/buildsystems/vcpkg.cmake
make -j4

  1. Use Visual Studio with the C++ development kit to build the project using the files generated in the build folder.
  2. Verify that Cortex.cpp is installed correctly by getting help information.

# Get the help information
cortex -h

Prerequisites​

Dependencies​

Windows​

  • Node.js version 18 and higher
  • NPM

Windows Subsystem for Linux​

  • Node.js version 18 and higher
  • NPM
  • Homebrew
  • Windows Subsystem for Linux (Ubuntu)
  • OpenMPI

Hardware​

Operating System​

  • Windows 10 or higher.

CPU​

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  • Cortex.cpp supports a processor that can handle AVX2. For the full list, please see here.
  • We support older processors with AVX and AVX-512, though this is not recommended.
Intel CPU​
  • Haswell processors (Q2 2013) and newer.
  • Tiger Lake (Q3 2020) and newer for Celeron and Pentium processors.
AMD CPU​
  • Excavator processors (Q2 2015) and newer.

RAM​

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We support DDR2 RAM as the minimum requirement but recommend using newer generations of RAM for improved performance.

  • 8GB for running up to 3B models (int4).
  • 16GB for running up to 7B models (int4).
  • 32GB for running up to 13B models (int4).

GPU​

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Having at least 6GB VRAM when using NVIDIA, AMD, or Intel Arc GPUs is recommended.

  • 6GB can load the 3B model (int4) with ngl at 120 ~ full speed on CPU/ GPU.
  • 8GB can load the 7B model (int4) with ngl at 120 ~ full speed on CPU/ GPU.
  • 12GB can load the 13B model (int4) with ngl at 120 ~ full speed on CPU/ GPU.
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Disk​

  • At least 10GB for app storage and model download.