AI/ML
Deploy LLaMA 3.3 in Docker with Ollama on AWS EC2 - Step by Step Guide
LLaMA 3.3 Model for your Business?
Cost Efficiency (Open Source)
Lower Long Term costs
Customised data control
Pre trained model
Get Your LLaMA 3.3 AI Model Running in a Day
Free Installation Guide - Step by Step Instructions Inside!
Introduction
LLaMA 3.3 is a cutting edge AI model designed for text generation. Deploying it in a Docker container on an AWS EC2 instance ensures scalability, portability and ease of maintenance.
Prerequisites
Before starting, ensure you have:
- An AWS EC2 instance (Ubuntu recommended) with Docker installed.
- SSH access to the instance.
Step 1: SSH into Your EC2 Instance
To begin, connect to your EC2 instance using SSH:
ssh -i your-key.pem ubuntu@your-ec2-public-ipOnce logged in, update the system:
sudo apt update && sudo apt upgrade -yStep 2: Start an Ollama Docker Container
Deploy the Ollama container with persistent storage:
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollamaStep 3: Enter the Container
Access the running container using:
docker exec -it ollama /bin/bashStep 4: Fetch LLaMA 3.3 Model
Inside the container, download the LLaMA 3.3 model:
ollama pull llama3.3Step 5: Running the Model
To start generating text, execute:
ollama run llama3.3
Test it with an example query:
>>> Explain quantum computing in simple terms.Step 6: Deploy a Web UI for Interaction
For an intuitive interface, deploy Open WebUI:
docker run -d -p 3000:8080 -eOLLAMA_BASE_URL=http://<YOUR-IP>:11434 -vopen-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main Now, open http://<YOUR-IP>:3000 in your browser to interact with LLaMA 3.3.
Conclusion
With Docker and Ollama, running LLaMA 3.3 on an AWS EC2 instance is simple and efficient. This setup ensures scalability and flexibility for AI-driven text generation.
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AI/ML