AI/ML
Complete Guide to Installing Dolphin-Mixtral on Azure VM Using Docker and Ollama
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Free Installation Guide - Step by Step Instructions Inside!
Introduction
Dolphin-Mixtral is a powerful AI model designed for advanced natural language processing. Hosting it in a Docker container on an Azure Virtual Machine (VM) allows for seamless deployment, scalability and an isolated execution environment.
Provisioning the Azure VM
Ensure you have an Ubuntu-based Azure VM ready. If you haven’t created one yet, set it up via the Azure Portal or Azure CLI.
Once the VM is running, connect to it via SSH:
ssh -i your-private-key.pem azure-user@your-vm-ip
Update your system packages before proceeding:
sudo apt update && sudo apt upgrade -y
If Docker is not installed, install it using:
sudo apt install docker.io -ysudo systemctl start dockersudo systemctl enable docker
Deploying Ollama
Now, pull and run the Ollama container, which will manage Dolphin-Mixtral:
docker run -d --name ollama -p 11434:11434 -v ollama:/root/.ollama ollama/ollamaVerify the container is running:
docker ps
Fetching Dolphin-Mixtral Model
Once the Ollama container is running, install Dolphin-Mixtral inside it:
docker exec -it ollama /bin/bash
Now write this command from inside the container:
ollama pull dolphin-mixtral
This will download all necessary dependencies.
Running Dolphin-Mixtral
To start using the model, execute:
ollama run dolphin-mixtral Test the model with a prompt:
>>> How does blockchain technology work?
If the response is generated, the model is functioning correctly.
Web-Based Interaction with Dolphin-Mixtral
To access Dolphin-Mixtral through a browser-based UI, deploy Open WebUI:
docker run -d --name ollama-ui -p 5050:8080 -eOLLAMA_BASE_URL=http://<YOUR-VM-IP>:11434 -vopen-webui:/app/backend/data --restartalways ghcr.io/open-webui/open-webui:main
Now, navigate to http://<YOUR-VM-IP>:5050 to interact with the model via a user-friendly interface.
Final Thoughts
Deploying Dolphin-Mixtral on an Azure VM using Docker & Ollama ensures efficient performance in an isolated environment. Whether you prefer CLI based interactions or a web UI, this setup offers a seamless AI deployment experience.
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