Step by step walk though of how to install instructlab on Fedora 40
Drivers and CUDA Toolkit Setup for Nvidia on Fedora 40
First determine what driver is installed. Below we can see that we are running the "nouveau" driver and not the Nvidia proprietary driver. $ sudo lspci -n -n -k | grep -A 2 -e VGA -e 3D 01:00.0 VGA compatible controller [0300]: NVIDIA Corporation GA106 [GeForce RTX 3060 Lite Hash Rate] [10de:2504] (rev a1) Subsystem: … Continue reading Drivers and CUDA Toolkit Setup for Nvidia on Fedora 40
Homelab: Shushing a loud Dell Server.
Rack mount servers are notoriously loud. They are designed to run in data centers which and not next to your head. In a data center no one really notices or cares if a machine's fans are spinning faster than they need to. 2RU Servers are bad, but 1U are even worse as the smaller the … Continue reading Homelab: Shushing a loud Dell Server.
Step-by-Step Nvidia CUDA Toolkit Installation Guide: Ubuntu 24.04
The NVIDIA CUDA Toolkit is essential for developing GPU-accelerated applications and includes various tools. Users must uninstall older versions from Ubuntu before installing the latest toolkit from NVIDIA’s website for better performance and compatibility. The summary highlights differences between installation methods regarding version availability, ease, and update management.
Step-by-Step Nvidia CUDA Toolkit Installation Guide: Ubuntu 22.04
"The NVIDIA CUDA Toolkit is a software development kit that helps users create GPU-accelerated applications. It includes libraries, compilers, debuggers, and optimization tools". Since we have an Nvidia GPU we will install it as shown below. Note: If you installed the nvidia-cuda-toolkit from default ubuntu noble repo, uninstall it first as that version is probably too old. … Continue reading Step-by-Step Nvidia CUDA Toolkit Installation Guide: Ubuntu 22.04
Getting Started with RamaLama with Nvidia Cuda Support On Ubuntu 24.04
Introduction to RamaLama Streamlining AI Deployment with OCI Containers RamaLama is an open-source project developed to simplify AI model deployment and management using OCI (Open Container Initiative) containers. Ramalama enables seamless execution of AI workloads across different hardware configurations, supporting both GPU-accelerated and CPU-based environments. By leveraging container engines like Podman and Docker, RamaLama includes … Continue reading Getting Started with RamaLama with Nvidia Cuda Support On Ubuntu 24.04
Essential Python Pip Commands for Linux Administrators
This blog post explores how to effectively manage Python packages using pip. Learn how to install and uninstall packages, handle dependencies, and clean up unused libraries to keep your environment organized. We also cover tools like pip-autoremove and best practices for dependency management. Whether you're a beginner or an experienced developer, this guide will help you streamline your Python package management workflow.