🦙 Local LLaMA 3 Chat: Fast, Private, and Fully Offline AI
I built and deployed a local instance of Meta’s powerful LLaMA 3 8B Instruct model, running directly on my own infrastructure — with no internet connection required.
Using llama-cpp-python, I created a custom Streamlit web app that allows real-time conversation with the model via a browser interface. Everything runs on my own CPU-based server, optimized for performance and privacy.
🔧 Key Features:
- 🧠 LLaMA 3 8B Q4_K_M model running fully locally
- 🗣️ Supports real-time chat with instruction-following
- 🚀 Optimized with
llama-cpp-pythonfor high-speed inference - 💬 Simple browser-based frontend using Streamlit
- 🧹 No chat history (stateless, single-turn replies)
- ⛔ No cloud APIs, no data sent to external servers
- 📂 Models stored and managed locally using GGUF format
This project combines AI performance with data sovereignty, ideal for experimenting with local LLMs and building privacy-focused applications.