Installing Ollama and Running DeepSeek Locally

This guide will walk you through the process of installing Ollama and running the DeepSeek language model on your local machine.

Prerequisites

• A system running macOS, Windows, or Linux
• At least 8GB of RAM (16GB+ recommended)
• An internet connection (for downloading the model)
• Optional: GPU support for better performance

What is Ollama?

Ollama is a simple and efficient way to run large language models locally. It offers a command-line interface and takes care of model downloading, execution, and environment setup behind the scenes.

Steps to Install and Run DeepSeek Locally

1. Install Ollama

Visit Ollama's official website and download the installer for your OS:

• macOS: Use the .pkg installer or install via Homebrew:

  bash

  Copy

  1brew install ollama

• Windows: Download and run the .exe installer.

• Linux: Run the following script in your terminal:

  text

  Copy

  1curl -fsSL https://ollama.com/install.sh | sh

After installation, verify Ollama is working by running:

1ollama --version

2. Run the DeepSeek Model

Ollama uses a simple pull-and-run system. To download and run the DeepSeek model:

1ollama run deepseek

This command will automatically:

• Download the DeepSeek model if it’s not already cached
• You can start chatting with the model immediately after it loads.

⚠️ Depending on the size of the model and your internet speed, the initial pull may take a few minutes.

3. List Available Models

To explore other models Ollama supports:

1ollama list

And to remove any model:

1ollama remove <model-name>

4. Run DeepSeek in the Background (Optional)

If you want to serve DeepSeek continuously in the background:

1ollama serve &

You can now make requests via API to http://localhost:11434 or use it in apps like LM Studio, Obsidian, or VSCode extensions that support custom LLM endpoints.

5. Customize the DeepSeek Model (Optional)

You can create a custom Modelfile to tweak how DeepSeek behaves. Example:

1FROM deepseek
2PARAMETER temperature 0.7

Then run:

1ollama create deepseek-custom -f Modelfile
2ollama run deepseek-custom

Troubleshooting Tips

• Model download fails: Make sure you're connected to the internet and not behind a restrictive firewall.
• Not enough RAM: Try a smaller model, or run Ollama on a machine with more resources.
• API not responding: Ensure the Ollama server is running. You can restart it with ollama serve.

Conclusion

You're now set up to run DeepSeek locally using Ollama! This is a great way to experiment with open-source language models without relying on the cloud. For more details, check out the Ollama documentation or the DeepSeek GitHub.