What if you could carry the equivalent of 127 million novels or the entire Wikipedia 2,500 times over… in your pocket? With the Dolphin-LLaMA3 model from Hugging Face (via Ollama), you can. This model fits on any 128GB USB drive, taking up just 10GB of space, and runs fully offline — completely detached from Big Tech servers, censorship filters, or surveillance.

Contents

• About the Model
• Routine Overview
• Initial Setup on Windows
• Running from a USB Drive
• Running AI from the USB
• Improve the Interface with AnythingLLM
• Interacting with Dolphin via Python (API)
• Final Thoughts

🧠 About the Model

We’ll be using the Dolphin-LLaMA3 model, available directly through Ollama. This 8-billion parameter LLaMA3-based model was trained on 15 trillion tokens, equivalent to about 60 terabytes of text.

You did what?!

Let me explain: You write your notes in your Vault. Then, you run a command, and the code inside becomes a script and executes! And it does so with the environment of your choice already activated.

Oh, I see now. This is a notebook!

No, it’s not. It transforms every code block—including comments—into an independent script.py inside your .obsidian\scripts\python folder. From there, you can grab it and start deploying or packaging it.

From: Ollama Installation. To: AI Integration

Inspired once more by NetworkChuck, this guide walks you through setting up Ollama on your system, integrating various AI models, and enhancing your workflow with ==Stable Diffusion== and ==BMO== or ==Smart Connections== on obsidian. Whether you’re a developer or an AI enthusiast, this step-by-step tutorial will help you harness the power of local AI models effectively.

If you also enjoy configuring your AI environment and exploring different models, this approach will provide you with the control and flexibility you need!

From: Vault’s folder. To: Blog’s feed This is my personal blogging pipeline, inspired by the content creator NetWorkChuck. I hope this guide helps you express your ideas more effectively and share them with the world.

If you enjoy maintaining control over your publications and having some code-based automation fun, this approach should serve you well!

What’s happening here is that an Obsidian vault is feeding the content of the posts you’re reading right now. Once everything is set up, the process requires minimal effort to keep running smoothly.