Getting Started¶
This is a guide on getting started with GPT-in-a-Box deployment on a Virtual Machine. You can find the open source repository for the virtual machine version here.
Tested Specifications:
| Specification | Tested Version |
|---|---|
| Python | 3.10 |
| Operating System | Ubuntu 20.04 |
| GPU | NVIDIA A100 40G |
| CPU | 8 vCPUs |
| System Memory | 32 GB |
Follow the steps below to install the necessary prerequisites.
Install openjdk, pip3¶
Run the following command to install pip3 and openjdk
sudo apt-get install openjdk-17-jdk python3-pip
Install NVIDIA Drivers¶
To install the NVIDIA Drivers, refer to the official Installation Reference.
Proceed to downloading the latest Datacenter NVIDIA drivers for your GPU type.
For NVIDIA A100, Select A100 in Datacenter Tesla for Linux 64 bit with CUDA toolkit 11.7, latest driver is 515.105.01.
curl -fSsl -O https://us.download.nvidia.com/tesla/515.105.01/NVIDIA-Linux-x86_64-515.105.01.run
sudo sh NVIDIA-Linux-x86_64-515.105.01.run -s
Note
There is no need to install CUDA toolkit separately as it is bundled with PyTorch installation. The NVIDIA driver installation is sufficient.
Download Nutanix package¶
Download the v0.3 release version from the NAI-LLM Releases and untar the release on the node. Set the working directory to the root folder containing the extracted release.
export WORK_DIR=absolute_path_to_empty_release_directory
mkdir $WORK_DIR
tar -xvf <release tar file> -C $WORK_DIR --strip-components=1
Install required packages¶
Run the following command to install the required python packages.
pip install -r $WORK_DIR/llm/requirements.txt