Installing and Using DeepSeek-R1:1.5 on a Raspberry Pi with Docker Learn how to install and use DeepSeek-R1:1.5 on your Raspberry Pi using Docker. 26 January 2025 3 minute read By Kevin McAleer Share this article on Table of Contents IntroductionWhy DeepSeek-R1:1.5?Installation RequirementsStep 1: Install Docker and Docker ComposeStep 2: Download my ClusteredPi docker respositoryStep 3: Run the Docker Compose FileStep 4: Log into the Open-WebUIStep 5: Grab the deepseek-r1:1.5b modelPros and Cons of DeepSeek-R1:1.5ProsConsHow DeepSeek-R1:1.5 Challenges ChatGPT and GeminiFinal thoughts Tags: Raspberry Pi ai MicroPython Difficulty: beginner Category: robotics ai raspberrypi Code: https://www.github.com/kevinmcaleer/ollama-python Home Blog Installing and using deepseek r1:1.5 on a raspberry pi with docker Installing and Using DeepSeek-R1:1.5 on a Raspberry Pi with Docker Learn how to install and use DeepSeek-R1:1.5 on your Raspberry Pi using Docker. 26 January 2025 | 3 minute read | By Kevin McAleer | Share this article on Page last updated 26 January 2025 Video For every project I create, I often make a corresponding YouTube video. Sometimes, there might be more than one video for a single project. You can find these videos in this section. Explore more through this this dedicated video. Introduction DeepSeek-R1:1.5 is an advanced AI model designed to deliver cutting-edge natural language processing (NLP) capabilities on lightweight devices. With its compact design and efficient architecture, DeepSeek-R1:1.5 is a powerful alternative to mainstream models like ChatGPT and Gemini, proving that high-performance AI can thrive outside the realm of massive cloud infrastructure. This guide will walk you through installing and running DeepSeek-R1:1.5 on a Raspberry Pi using Docker. Why DeepSeek-R1:1.5? DeepSeek-R1:1.5 is a groundbreaking AI model for the following reasons: Compact Efficiency: Optimized for resource-constrained devices like Raspberry Pi, it delivers impressive NLP performance without heavy GPU or cloud reliance. Privacy-Centric Design: By running locally, it ensures that sensitive data remains on the device, offering unparalleled user privacy. Customization: Developers can fine-tune it to fit specific use cases, making it highly adaptable for personal and professional projects. Cost-Effective: Unlike subscription-based models like ChatGPT or Gemini, DeepSeek is open-source and free to run locally. While it may not yet surpass the conversational depth of larger models, its innovative approach pushes the boundaries of on-device AI. Installation Requirements To run DeepSeek-R1:1.5 on your Raspberry Pi, you’ll need: A Raspberry Pi 5 or higher (8GB RAM recommended for optimal performance, 16Gb works nicely too!). Docker and Docker Compose installed. Internet connection for initial image download. MicroSD card with at least 32GB of storage. Step 1: Install Docker and Docker Compose Start by installing Docker and Docker Compose on your Raspberry Pi: Follow the detailed instructions here: Install Docker Verify the installation: docker --version docker-compose --version Step 2: Download my ClusteredPi docker respository Pull my ClusteredPi repository from GitHub (which contains the docker-compose file for Ollama & Open-WebUI): git clone https://www.github.com/kevinmcaleer/ClusteredPi.git Step 3: Run the Docker Compose File Navigate to the ClusteredPi/stacks/ollama folder and bring up the docker containers: cd ClusteredPi/stacks/ollama docker-compose up -d This will pull the Ollama and Open-WebUI images from Docker Hub and start the containers in the background. Step 4: Log into the Open-WebUI Open a browser to http://<your-pi-ip>:3000 and create an account. Once you have created an account, you can log in and start using the Open-WebUI. Step 5: Grab the deepseek-r1:1.5b model Once you are logged into Open-WebUI: Click on the user icon Click on Admin panel Click on Setting Click on Models Click into the Pull a model from Ollama.com textbox Type deepseek-r1:1.5b - for the smallest model Once downloaded click on New Chat and try it out for yourself! Pros and Cons of DeepSeek-R1:1.5 Pros Lightweight: Optimized for edge devices, making it accessible to hobbyists and developers. Privacy: Data stays on the device, addressing privacy concerns. Customizable: Open-source and adaptable to various use cases. Affordable: No ongoing costs compared to cloud-based AI services. Cons Performance Limitations: Lacks the computational power of cloud-based models like ChatGPT and Gemini. Initial Setup Complexity: Requires technical knowledge to install and configure. Limited Ecosystem: Fewer integrations and community support compared to mainstream models. How DeepSeek-R1:1.5 Challenges ChatGPT and Gemini DeepSeek-R1:1.5 is a disruptive innovation in the AI landscape for several reasons: On-Device AI: By focusing on local deployment, it eliminates the dependency on powerful servers, making AI more accessible and environmentally friendly. Privacy by Design: Its local-first approach caters to users wary of cloud data breaches or surveillance. Democratization of AI: Open-source availability allows developers to harness its power without corporate barriers. Edge Computing Revolution: Pioneers AI use cases in edge computing, opening doors for innovative IoT applications. While ChatGPT and Gemini excel in sheer scale and capabilities, DeepSeek-R1:1.5 proves that smaller, specialized models can carve their niche in the rapidly evolving AI world. Final thoughts DeepSeek-R1:1.5 is a remarkable step forward in making advanced AI accessible on low-power devices like the Raspberry Pi. Its privacy-first design, affordability, and flexibility make it a compelling alternative to big players like ChatGPT and Gemini. By following this guide, you can unleash the potential of DeepSeek-R1:1.5 and explore new possibilities in local AI deployment. Code View Code Repository on GitHub - https://www.github.com/kevinmcaleer/ollama-python Liked this article? You might like these too. Pi Tray - Mini-rack - Part II In this part of the mini-rack project, we will finish the design with the Pi Tray, Top Panel and Front Cluster Panel Pi 10 Inch Mini-rack A mini-rack is a great way to keep your equipment organized and easily accessible. Gamepad & BurgerBot Build a Raspberry Pi Pico powered bluetooth remote control for your robot 10 Projects for your Raspberry Pi Pico If you've just got a new Raspberry Pi Pico and you're looking for some inspiration, then you've come to the right place. Here is a collection of projects that you can build with your Raspberry Pi Pico. Raspberry Pi Telegraf Setup with Docker "Learn how to set up Telegraf on your Raspberry Pi with Docker to monitor system metrics and integrate with popular time-series databases like InfluxDB or Prometheus." Setting Up Dynamic DNS on a Raspberry Pi for Self-Hosting Learn how to configure Dynamic DNS on your Raspberry Pi to enable easy remote access and self-host your WordPress, Ghost blog, or other web services.
Installing and Using DeepSeek-R1:1.5 on a Raspberry Pi with Docker Learn how to install and use DeepSeek-R1:1.5 on your Raspberry Pi using Docker. 26 January 2025 3 minute read By Kevin McAleer Share this article on Table of Contents IntroductionWhy DeepSeek-R1:1.5?Installation RequirementsStep 1: Install Docker and Docker ComposeStep 2: Download my ClusteredPi docker respositoryStep 3: Run the Docker Compose FileStep 4: Log into the Open-WebUIStep 5: Grab the deepseek-r1:1.5b modelPros and Cons of DeepSeek-R1:1.5ProsConsHow DeepSeek-R1:1.5 Challenges ChatGPT and GeminiFinal thoughts Tags: Raspberry Pi ai MicroPython Difficulty: beginner Category: robotics ai raspberrypi Code: https://www.github.com/kevinmcaleer/ollama-python
Introduction DeepSeek-R1:1.5 is an advanced AI model designed to deliver cutting-edge natural language processing (NLP) capabilities on lightweight devices. With its compact design and efficient architecture, DeepSeek-R1:1.5 is a powerful alternative to mainstream models like ChatGPT and Gemini, proving that high-performance AI can thrive outside the realm of massive cloud infrastructure. This guide will walk you through installing and running DeepSeek-R1:1.5 on a Raspberry Pi using Docker. Why DeepSeek-R1:1.5? DeepSeek-R1:1.5 is a groundbreaking AI model for the following reasons: Compact Efficiency: Optimized for resource-constrained devices like Raspberry Pi, it delivers impressive NLP performance without heavy GPU or cloud reliance. Privacy-Centric Design: By running locally, it ensures that sensitive data remains on the device, offering unparalleled user privacy. Customization: Developers can fine-tune it to fit specific use cases, making it highly adaptable for personal and professional projects. Cost-Effective: Unlike subscription-based models like ChatGPT or Gemini, DeepSeek is open-source and free to run locally. While it may not yet surpass the conversational depth of larger models, its innovative approach pushes the boundaries of on-device AI. Installation Requirements To run DeepSeek-R1:1.5 on your Raspberry Pi, you’ll need: A Raspberry Pi 5 or higher (8GB RAM recommended for optimal performance, 16Gb works nicely too!). Docker and Docker Compose installed. Internet connection for initial image download. MicroSD card with at least 32GB of storage. Step 1: Install Docker and Docker Compose Start by installing Docker and Docker Compose on your Raspberry Pi: Follow the detailed instructions here: Install Docker Verify the installation: docker --version docker-compose --version Step 2: Download my ClusteredPi docker respository Pull my ClusteredPi repository from GitHub (which contains the docker-compose file for Ollama & Open-WebUI): git clone https://www.github.com/kevinmcaleer/ClusteredPi.git Step 3: Run the Docker Compose File Navigate to the ClusteredPi/stacks/ollama folder and bring up the docker containers: cd ClusteredPi/stacks/ollama docker-compose up -d This will pull the Ollama and Open-WebUI images from Docker Hub and start the containers in the background. Step 4: Log into the Open-WebUI Open a browser to http://<your-pi-ip>:3000 and create an account. Once you have created an account, you can log in and start using the Open-WebUI. Step 5: Grab the deepseek-r1:1.5b model Once you are logged into Open-WebUI: Click on the user icon Click on Admin panel Click on Setting Click on Models Click into the Pull a model from Ollama.com textbox Type deepseek-r1:1.5b - for the smallest model Once downloaded click on New Chat and try it out for yourself! Pros and Cons of DeepSeek-R1:1.5 Pros Lightweight: Optimized for edge devices, making it accessible to hobbyists and developers. Privacy: Data stays on the device, addressing privacy concerns. Customizable: Open-source and adaptable to various use cases. Affordable: No ongoing costs compared to cloud-based AI services. Cons Performance Limitations: Lacks the computational power of cloud-based models like ChatGPT and Gemini. Initial Setup Complexity: Requires technical knowledge to install and configure. Limited Ecosystem: Fewer integrations and community support compared to mainstream models. How DeepSeek-R1:1.5 Challenges ChatGPT and Gemini DeepSeek-R1:1.5 is a disruptive innovation in the AI landscape for several reasons: On-Device AI: By focusing on local deployment, it eliminates the dependency on powerful servers, making AI more accessible and environmentally friendly. Privacy by Design: Its local-first approach caters to users wary of cloud data breaches or surveillance. Democratization of AI: Open-source availability allows developers to harness its power without corporate barriers. Edge Computing Revolution: Pioneers AI use cases in edge computing, opening doors for innovative IoT applications. While ChatGPT and Gemini excel in sheer scale and capabilities, DeepSeek-R1:1.5 proves that smaller, specialized models can carve their niche in the rapidly evolving AI world. Final thoughts DeepSeek-R1:1.5 is a remarkable step forward in making advanced AI accessible on low-power devices like the Raspberry Pi. Its privacy-first design, affordability, and flexibility make it a compelling alternative to big players like ChatGPT and Gemini. By following this guide, you can unleash the potential of DeepSeek-R1:1.5 and explore new possibilities in local AI deployment.