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language:
- cs
- sk
- en
- de
license: apache-2.0
base_model: EuroLLM-9B
quantization: Q8_0
tags:
- gguf
- llama.cpp
- offline
- local-ai
- multilingual
- cli-runtime
- ai-runtime
pipeline_tag: text-generation
library_name: llama.cpp
---
# Offline AI 2.2 – EuroLLM-9B-Q8_0 (GGUF)
Offline AI 2.2 is a fully local AI runtime environment built around digital sovereignty, privacy, and system autonomy.
No cloud.
No telemetry.
No tracking.
No external dependencies.
Everything runs locally via **llama.cpp**.
---
## 🖥️ CLI Preview
Below is the Offline AI runtime interface:

Offline AI is no longer just a model launcher.
It is a **local AI runtime environment** designed to manage and operate language models fully offline with a structured command interface.
Core capabilities include:
- CLI runtime environment
- Model lifecycle management
- Profile-based workspace system
- Snapshot conversation archiving
- Runtime diagnostics and monitoring
- Administrative control layer
The architecture is designed as a foundation for **multi-model local AI systems**.
---
## 🧠 RUNTIME ARCHITECTURE
Offline AI uses a layered architecture:
User (CLI)
↓
Python Runtime
↓
C++ Inference Engine (llama.cpp)
↓
GGUF Language Model
The Python runtime acts as the **control layer**, responsible for:
- command handling
- model orchestration
- workspace profiles
- snapshots and notes
- system diagnostics
- administrative operations
The inference backend is a lightweight C++ wrapper around **llama.cpp** with real-time token streaming.
---
## 🔧 TECHNICAL INFORMATION
Base model: EuroLLM-9B
Quantization: Q8_0 (GGUF)
Format: llama.cpp compatible
Inference engine: llama.cpp
Offline AI Version: 2.2
Recommended RAM: 16 GB
Platforms: macOS, Windows, Linux
This repository distributes a **quantized GGUF Q8_0 variant** of the EuroLLM-9B model optimized for efficient local inference.
The original model weights are **not modified and not fine-tuned** as part of this project.
---
## 🚀 WHAT'S NEW IN 2.2
- Structured CLI runtime environment
- Model lifecycle management system
- Model alias system
- Workspace profiles and isolation
- Snapshot conversation archiving
- Runtime diagnostics and monitoring
- Administrative control mode
- Improved modular runtime architecture
Offline AI 2.2 evolves the project from a simple model launcher into a **local AI runtime platform** prepared for managing multiple specialized AI models.
---
## 🔐 PROJECT PHILOSOPHY
Offline AI demonstrates that modern AI systems can operate fully offline.
The project explores the idea that:
- AI does not require cloud infrastructure
- Open models can run independently on personal hardware
- AI tools can respect user privacy
- Local-first computing is a viable architecture
Offline AI promotes:
- Digital sovereignty
- Transparent system design
- Offline experimentation
- User-controlled AI environments
---
## 📄 MODEL ORIGIN & LICENSE
Model: EuroLLM-9B
Original authors: EuroLLM Project consortium
Funded by: European Union research initiatives
Base model license: Apache License 2.0
Quantized distribution: GGUF Q8_0
Runtime engine: llama.cpp (MIT License)
Offline AI runtime interface: © David Káninský
All components are used in compliance with their respective licenses.
---
## ⚠️ DISCLAIMER
This project is an educational and experimental implementation.
It is not a commercial AI service and does not replace professional advice.
Outputs are not intended for legal, medical, financial, or critical decision-making use.
Use beyond personal, research, or educational purposes is at your own responsibility.
---
## 🌍 PROJECT
Website: https://OfflineAI.online
Domains: .cz / .sk / .de
Offline AI Runtime
Author: David Káninský
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