Running Ollama with Docker: A Step-by-Step Guide

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There's a great way to get open source projects, like Ollama, running quickly on your system, that's Docker. Imagine this, once you have Docker installed, there's only one simple command to execute, and you’re done. To get started, execute a command that involves Ollama, a lot.

It seems they really want you to be familiar with that name! It gets a little technical, but it’s pretty easy. It's all about starting a container and giving access to a port. After that, you can run commands and things start running on your system.

Now, to make it work, you need to call out to Docker, pinpoint the running containers, and type in your chosen model and a complete prompt. Once it's set up, you can run any of the models using Docker. The best part is, you don't need to install the models directly.

Even if a model isn't available, Ollama will still recognize it. All your data can be stored in an Ollama folder through a, UB function. Then you just type the prompt, hit enter, and your system runs like a well-oiled machine.

For example, if you ask for another word for run, it might reply, "stride," and explain what it means. It's like a Q&A assistant, which could then be asked for another word for llama. Strangely enough, it might answer, "camel." Remember, model size matters! Smaller models need less disk space and run faster but may not provide as detailed responses.

Large models can be more powerful but require more system resources. An interesting experiment would be to ask it for help improving your business' social media presence. It might give you surprisingly helpful advice like, "develop a consistent tone and personality." That’s pretty insightful! The amazing takeaway is that you can now run your own AI models right from your own hardware, without needing to pay for external vendors.