1 line
2.2 KiB
HTML
1 line
2.2 KiB
HTML
<!DOCTYPE html><html><head><meta charset="utf-8"><meta http-equiv="Content-Security-Policy" content="upgrade-insecure-requests"><meta name="viewport" content="width=device-width, initial-scale=1.0"><link type="text/css" rel="stylesheet" href="/style.css"><link type="text/css" rel="stylesheet" href="style.css"><title>Mirrored Gemini content.</title></head><body><h1> Getting Started with Ollama: Running Large Language Models Locally</h1><p>Ollama is a tool that allows you to run powerful large language models (LLMs) on your own computer. This guide will walk you through the steps of downloading, installing, and using Ollama to interact with LLMs.</p><h2> Guide</h2><p>1. Check Your GPU (Optional):</p><p>Ollama can leverage your computer's graphics processing unit (GPU) for faster performance.</p><p>During installation, Ollama will automatically detect your GPU.</p><p>Make sure you have the latest drivers installed for your NVIDIA or AMD GPU for optimal performance.</p><p>2. Download and Install Ollama:</p><p>Head over to the official Ollama website: https://ollama.com/</p><p>Use the installer for your operating system (Mac, Windows, or Linux).</p><p>3. Download a Large Language Model:</p><p>Ollama supports various open-source LLMs. You can browse available models on the Ollama blog: https://ollama.com/models</p><p>Use the ollama pull command followed by the model name to download an LLM. For example: ```ollama pull llama3```</p><p>4. Run the LLM:</p><p>Start Ollama using the ollama run command followed by the model name. For instance: ```ollama run llama3```</p><p>This will launch the Ollama REPL (Read-Eval-Print Loop) where you can interact with the LLM.</p><p>5. Interact with the LLM:</p><p>Type your prompts and questions in the Ollama REPL.</p><p>The LLM will respond based on its understanding of your input.</p><p>You can experiment with different prompts and see how the LLM generates text, translates languages, writes different kinds of creative content, and answers your questions in an informative way.</p><h2> Additional Resources:</h2><p>Ollama Documentation: https://github.com/ollama/ollama offers detailed guides on installation, using specific LLM features, and integrating Ollama with Python and other tools.</p></body></html>
|