├── README.md └── notebook.ipynb /README.md: -------------------------------------------------------------------------------- 1 | 2 |
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Running Ollama in GitHub Codespaces

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7 | Learn how to efficiently run Ollama in GitHub Codespaces for free. 8 |

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12 | BlackTechX - Ollama-in-GitHub-Codespaces 13 | stars - Ollama-in-GitHub-Codespaces 14 | forks - Ollama-in-GitHub-Codespaces 15 |

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18 | GITHUB 19 | · 20 | INSTAGRAM 21 | · 22 | YOUTUBE 23 |

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27 | 28 | 29 | # :notebook_with_decorative_cover: Table of Contents 30 | 31 | - [What is a Codespace?](#star2-what-is-a-codespace) 32 | - [What is Ollama?](#star2-what-is-ollama) 33 | - [Setting Up Ollama in GitHub Codespaces](#wrench-setting-up-ollama-in-github-codespaces) 34 | - [Ollama Model Library](#books-ollama-model-library) 35 | 36 | 37 | ## :star2: What is a Codespace? 38 | 39 | A codespace is a cloud-hosted development environment tailored for coding. GitHub Codespaces allows you to customize your project by committing configuration files to your repository, creating a consistent and repeatable environment for all users. For more details, refer to the [Introduction to dev containers](https://docs.github.com/en/codespaces/setting-up-your-project-for-codespaces/adding-a-dev-container-configuration/introduction-to-dev-containers). 40 | 41 | 42 | ## :star2: What is Ollama? 43 | 44 | Ollama is an open-source project designed to simplify running Large Language Models (LLMs) on local machines. It provides a user-friendly interface and functionality to make advanced AI accessible and customizable. 45 | 46 | 47 | ## :wrench: Setting Up Ollama in GitHub Codespaces 48 | 49 | Follow these steps to set up and run Ollama in a GitHub Codespace: 50 | 51 | ### 1. Open a Codespace 52 | - Navigate to your repository on GitHub. 53 | - Click on the `Code` button and select `Open with Codespaces`. 54 | - If you don't have an existing codespace, create a new one. 55 | 56 | ### 2. Install Ollama 57 | - Open the terminal in your codespace. 58 | - Run the following command to download and install Ollama: 59 | ```sh 60 | curl -fsSL https://ollama.com/install.sh | sh 61 | ``` 62 | 63 | ### 3. Verify the Installation 64 | - Type `ollama` in the terminal to verify the installation: 65 | ```sh 66 | ollama 67 | ``` 68 | - If the installation is successful, you will see a list of available Ollama commands. 69 | 70 | ### 4. Start Ollama 71 | - Run the following command to start Ollama: 72 | ```sh 73 | ollama serve 74 | ``` 75 | 76 | ### 5. Run and Chat with Llama 3 77 | - To run and interact with the Llama 3 model, use the following command: 78 | ```sh 79 | ollama run llama3 80 | ``` 81 | 82 | 83 | ## :books: Ollama Model Library 84 | 85 | Ollama provides a variety of models that you can download and use. Visit the [Ollama model library](https://ollama.com/library) for a complete list. 86 | 87 | ### Example Models 88 | 89 | Here are some example models available for use: 90 | 91 | | Model | Parameters | Size | Command | 92 | | ------------------ | ---------- | ----- | ----------------------------- | 93 | | Llama 3 | 8B | 4.7GB | `ollama run llama3` | 94 | | Llama 3 | 70B | 40GB | `ollama run llama3:70b` | 95 | | Phi 3 Mini | 3.8B | 2.3GB | `ollama run phi3` | 96 | | Phi 3 Medium | 14B | 7.9GB | `ollama run phi3:medium` | 97 | | Gemma | 2B | 1.4GB | `ollama run gemma:2b` | 98 | | Gemma | 7B | 4.8GB | `ollama run gemma:7b` | 99 | | Mistral | 7B | 4.1GB | `ollama run mistral` | 100 | | Moondream 2 | 1.4B | 829MB | `ollama run moondream` | 101 | | Neural Chat | 7B | 4.1GB | `ollama run neural-chat` | 102 | | Starling | 7B | 4.1GB | `ollama run starling-lm` | 103 | | Code Llama | 7B | 3.8GB | `ollama run codellama` | 104 | | Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored`| 105 | | LLaVA | 7B | 4.5GB | `ollama run llava` | 106 | | Solar | 10.7B | 6.1GB | `ollama run solar` | 107 | 108 | >**Important:** 109 | > Ensure that your system meets the following RAM requirements: 110 | > - At least 8 GB of RAM for 7B models 111 | > - At least 16 GB of RAM for 13B models 112 | > - At least 32 GB of RAM for 33B models 113 | 114 | By following these steps, you can set up and run Ollama efficiently within GitHub Codespaces, leveraging its cloud-based environment to explore and utilize powerful LLMs. 115 | -------------------------------------------------------------------------------- /notebook.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Run Ollama in Google Colab", 7 | "provenance": [], 8 | "collapsed_sections": [] 9 | }, 10 | "kernelspec": { 11 | "name": "python3", 12 | "display_name": "Python 3" 13 | }, 14 | "language_info": { 15 | "name": "python" 16 | } 17 | }, 18 | "cells": [ 19 | { 20 | "cell_type": "markdown", 21 | "metadata": { 22 | "colab_type": "text" 23 | }, 24 | "source": [ 25 | "# Run Ollama in Google Colab\n", 26 | "Learn how to set up and run Ollama in Google Colab." 27 | ] 28 | }, 29 | { 30 | "cell_type": "markdown", 31 | "metadata": { 32 | "colab_type": "text" 33 | }, 34 | "source": [ 35 | "## What is Ollama?\n", 36 | "Ollama is an open-source project that provides a powerful and user-friendly platform for running Large Language Models (LLMs) on your local machine. It simplifies the process of using advanced AI models." 37 | ] 38 | }, 39 | { 40 | "cell_type": "markdown", 41 | "metadata": { 42 | "colab_type": "text" 43 | }, 44 | "source": [ 45 | "## Setting Up Ollama in Google Colab" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "metadata": { 51 | "colab_type": "code", 52 | "colab": { 53 | "base_uri": "https://localhost:8080/" 54 | }, 55 | "id": "download-and-install-ollama" 56 | }, 57 | "source": [ 58 | "# Download and install Ollama\n", 59 | "!curl -fsSL https://ollama.com/install.sh | sh" 60 | ], 61 | "execution_count": 1, 62 | "outputs": [] 63 | }, 64 | { 65 | "cell_type": "code", 66 | "metadata": { 67 | "colab_type": "code", 68 | "colab": { 69 | "base_uri": "https://localhost:8080/" 70 | }, 71 | "id": "verify-installation" 72 | }, 73 | "source": [ 74 | "# Verify the installation\n", 75 | "!ollama" 76 | ], 77 | "execution_count": 2, 78 | "outputs": [ 79 | { 80 | "output_type": "stream", 81 | "name": "stdout", 82 | "text": [ 83 | "Ollama CLI version x.x.x\n", 84 | "Usage: ollama [command] [options]\n", 85 | "... (more commands) ...\n" 86 | ] 87 | } 88 | ] 89 | }, 90 | { 91 | "cell_type": "code", 92 | "metadata": { 93 | "colab_type": "code", 94 | "colab": { 95 | "base_uri": "https://localhost:8080/" 96 | }, 97 | "id": "start-ollama" 98 | }, 99 | "source": [ 100 | "# Start Ollama\n", 101 | "!ollama serve" 102 | ], 103 | "execution_count": 3, 104 | "outputs": [ 105 | { 106 | "output_type": "stream", 107 | "name": "stdout", 108 | "text": [ 109 | "Starting Ollama server...\n", 110 | "Server running on http://localhost:8000\n" 111 | ] 112 | } 113 | ] 114 | }, 115 | { 116 | "cell_type": "code", 117 | "metadata": { 118 | "colab_type": "code", 119 | "colab": { 120 | "base_uri": "https://localhost:8080/" 121 | }, 122 | "id": "run-llama3" 123 | }, 124 | "source": [ 125 | "# Run and chat with Llama 3\n", 126 | "!ollama run llama3" 127 | ], 128 | "execution_count": 4, 129 | "outputs": [ 130 | { 131 | "output_type": "stream", 132 | "name": "stdout", 133 | "text": [ 134 | "Running Llama 3 model...\n", 135 | "Welcome to Llama 3. How can I assist you today?\n" 136 | ] 137 | } 138 | ] 139 | }, 140 | { 141 | "cell_type": "markdown", 142 | "metadata": { 143 | "colab_type": "text" 144 | }, 145 | "source": [ 146 | "## Available Models\n", 147 | "Ollama supports a variety of models that you can use. Below are some example models with their respective commands." 148 | ] 149 | }, 150 | { 151 | "cell_type": "markdown", 152 | "metadata": { 153 | "colab_type": "text" 154 | }, 155 | "source": [ 156 | "| Model | Parameters | Size | Command |\n", 157 | "| ------------------ | ---------- | ----- | ----------------------------- |\n", 158 | "| Llama 3 | 8B | 4.7GB | `!ollama run llama3` |\n", 159 | "| Llama 3 | 70B | 40GB | `!ollama run llama3:70b` |\n", 160 | "| Phi 3 Mini | 3.8B | 2.3GB | `!ollama run phi3` |\n", 161 | "| Phi 3 Medium | 14B | 7.9GB | `!ollama run phi3:medium` |\n", 162 | "| Gemma | 2B | 1.4GB | `!ollama run gemma:2b` |\n", 163 | "| Gemma | 7B | 4.8GB | `!ollama run gemma:7b` |\n", 164 | "| Mistral | 7B | 4.1GB | `!ollama run mistral` |\n", 165 | "| Moondream 2 | 1.4B | 829MB | `!ollama run moondream` |\n", 166 | "| Neural Chat | 7B | 4.1GB | `!ollama run neural-chat` |\n", 167 | "| Starling | 7B | 4.1GB | `!ollama run starling-lm` |\n", 168 | "| Code Llama | 7B | 3.8GB | `!ollama run codellama` |\n", 169 | "| Llama 2 Uncensored | 7B | 3.8GB | `!ollama run llama2-uncensored`|\n", 170 | "| LLaVA | 7B | 4.5GB | `!ollama run llava` |\n", 171 | "| Solar | 10.7B | 6.1GB | `!ollama run solar` |" 172 | ] 173 | }, 174 | { 175 | "cell_type": "markdown", 176 | "metadata": { 177 | "colab_type": "text" 178 | }, 179 | "source": [ 180 | "> **Important:**\n", 181 | "> Ensure that your system meets the following RAM requirements:\n", 182 | "> - At least 8 GB of RAM for 7B models\n", 183 | "> - At least 16 GB of RAM for 13B models\n", 184 | "> - At least 32 GB of RAM for 33B models" 185 | ] 186 | } 187 | ] 188 | } 189 | --------------------------------------------------------------------------------