Running DeepSeek on Linux: A Step-by-Step Guide
- AI, Linux Basics, System Administration, Virtualization, Web Servers
- June 12, 2025

In this tutorial, I’ll walk you through integrating M-Pesa’s Lipa na M-Pesa Online (STK Push) into your Node.js backend. This guide covers everything from setup to implementation with a clear folder structure. Prerequisites Before we begin, ensure you have: Project Structure Step 1: Initialize Project Create a new directory and initialize your Node.js project: Step
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Introduction Welcome to this comprehensive guide on setting up Ollama with a user interface on your Windows or Linux machine! In today’s AI-driven world, having access to powerful language models locally on your computer offers unprecedented privacy, control, and cost savings. Whether you’re a developer, researcher, or AI enthusiast, this guide will walk you through
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Introduction If you’re looking for the easiest way to set up Coolify on Ubuntu, you’re in the right place. This guide provides the most streamlined installation process possible, perfect for beginners and anyone who wants to save time. The Simplest Installation Method One-Command Installation Run this single command in your terminal: Alternative Easy Methods Complete
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This guide walks through setting up a local Kubernetes cluster, installing Kubeflow, and running an end-to-end ML pipeline (training and serving) with Kubeflow Pipelines and KServe. We’ll use a scikit-learn model example and show commands and sample outputs at each step. All commands are run on a Linux or macOS terminal unless noted otherwise.
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This guide shows how to install and run DeepSeek on Ubuntu or RHEL/CentOS using the simplest methods (Docker or prebuilt binaries). You’ll learn to download the model, run a prompt, and verify output.
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Learn how to install InstructLab on RHEL 9 (CPU-only) with this clear, step-by-step guide for seamless setup.
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