How to Set Up DeepSeek with Ollama and Docker (Step-by-Step Guide)

With the increasing demand for efficient and powerful AI models, DeepSeek has gained popularity for its advanced language processing capabilities. Ollama provides an easy way to run and manage AI models locally, making it an excellent choice for deploying DeepSeek on your machine.

In this guide, we’ll walk through the DeepSeek setup guide using Ollama, ensuring a smooth installation and configuration process.

🚀 What is DeepSeek?

DeepSeek is an open-source large language model (LLM) optimized for high-performance inference and fine-tuning. It is a powerful alternative to models like LLaMA, GPT, and Mistral. DeepSeek AI offers fast processing and scalable performance, making it ideal for research and development.

🏗️ What is Ollama?

Ollama is a simple and efficient framework for running AI models locally. It allows you to pull, run, and interact with LLMs without dealing with complex configurations. Ollama simplifies DeepSeek AI deployment for developers and researchers.

🛠️ Prerequisites

Before getting started, ensure you have the following installed:

Ollama (Install from Ollama.ai)

A system with sufficient GPU/CPU resources

Docker (optional, if running inside a container)

🔧 How to Install DeepSeek on Ollama?

For macOS & Linux

curl -fsSL https://ollama.ai/install.sh | sh

For Windows

Download and install from Ollama.ai.

Once installed, verify Ollama is working:

ollama version

📦 How to Pull the DeepSeek Model in Ollama?

Ollama allows you to run DeepSeek AI with a simple command:

ollama pull deepseek

This downloads and installs the DeepSeek LLM on your system.

🚀 How to Run DeepSeek AI Locally?

Once the model is downloaded, you can start using it:

ollama run deepseek

This will start an interactive chat session with DeepSeek AI.

⚙️ Customizing DeepSeek AI in Ollama

You can configure DeepSeek using a modelfile in Ollama. Create a custom Modelfile to specify settings like memory usage and system prompts.

Example:

FROM deepseek
PARAMETER temperature 0.7
PARAMETER max_tokens 4096

Then, build and run the custom model:

ollama create my-deepseek -f Modelfile
ollama run my-deepseek

🖥️ How to Use DeepSeek AI with the Ollama API

Ollama provides an API to integrate DeepSeek AI into your applications.

Run the Ollama server:

ollama serve

Then, send a request using curl:

curl http://localhost:11434/api/generate -d '{
  "model": "deepseek",
  "prompt": "What is DeepSeek?",
  "stream": false
}'

🏗️ Running DeepSeek AI in a Docker Container (Optional)

If you prefer using Docker, create a Dockerfile:

FROM ubuntu:latest

RUN apt update && apt install -y curl

RUN curl -fsSL https://ollama.ai/install.sh | sh

CMD ["ollama", "run", "deepseek"]

Then, build and run the container:

docker build -t deepseek-ollama .
docker run -it deepseek-ollama

🎯 Conclusion

You have now successfully set up DeepSeek AI using Ollama! Whether you're using it for research, chat applications, or AI-based automation, Ollama makes DeepSeek deployment easy.

If you want to extend this setup, consider fine-tuning DeepSeek or integrating it into web applications using frameworks like Next.js or FastAPI.

🚀 Next Steps

Experiment with different model parameters

Integrate DeepSeek AI into your web applications

Try fine-tuning DeepSeek on custom datasets