Instructions to use theBOrg32/Egyptian_qwen_mobile_version with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use theBOrg32/Egyptian_qwen_mobile_version with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="theBOrg32/Egyptian_qwen_mobile_version", filename="egyptian_qwen_model_q2.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use theBOrg32/Egyptian_qwen_mobile_version with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf theBOrg32/Egyptian_qwen_mobile_version # Run inference directly in the terminal: llama-cli -hf theBOrg32/Egyptian_qwen_mobile_version
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf theBOrg32/Egyptian_qwen_mobile_version # Run inference directly in the terminal: llama-cli -hf theBOrg32/Egyptian_qwen_mobile_version
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf theBOrg32/Egyptian_qwen_mobile_version # Run inference directly in the terminal: ./llama-cli -hf theBOrg32/Egyptian_qwen_mobile_version
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf theBOrg32/Egyptian_qwen_mobile_version # Run inference directly in the terminal: ./build/bin/llama-cli -hf theBOrg32/Egyptian_qwen_mobile_version
Use Docker
docker model run hf.co/theBOrg32/Egyptian_qwen_mobile_version
- LM Studio
- Jan
- Ollama
How to use theBOrg32/Egyptian_qwen_mobile_version with Ollama:
ollama run hf.co/theBOrg32/Egyptian_qwen_mobile_version
- Unsloth Studio new
How to use theBOrg32/Egyptian_qwen_mobile_version with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for theBOrg32/Egyptian_qwen_mobile_version to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for theBOrg32/Egyptian_qwen_mobile_version to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for theBOrg32/Egyptian_qwen_mobile_version to start chatting
- Pi new
How to use theBOrg32/Egyptian_qwen_mobile_version with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf theBOrg32/Egyptian_qwen_mobile_version
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "theBOrg32/Egyptian_qwen_mobile_version" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use theBOrg32/Egyptian_qwen_mobile_version with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf theBOrg32/Egyptian_qwen_mobile_version
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default theBOrg32/Egyptian_qwen_mobile_version
Run Hermes
hermes
- Docker Model Runner
How to use theBOrg32/Egyptian_qwen_mobile_version with Docker Model Runner:
docker model run hf.co/theBOrg32/Egyptian_qwen_mobile_version
- Lemonade
How to use theBOrg32/Egyptian_qwen_mobile_version with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull theBOrg32/Egyptian_qwen_mobile_version
Run and chat with the model
lemonade run user.Egyptian_qwen_mobile_version-{{QUANT_TAG}}List all available models
lemonade list
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)🇸🇾 Egyptian_Qwen-3.5-GGUF: Egyptian Dialect LLM for Edge & Mobile
🌟 Introduction
Run Egyptian Dialect AI anywhere — on your phone, tablet, or edge device.
We are proud to present Egyptian_Qwen-3.5-GGUF, the quantized, portable version of the first Large Language Model fine-tuned specifically for the Egyptian Arabic Dialect.
Built on Qwen 3.5 and converted to the GGUF format, this model brings authentic Egyptian Arabic understanding to resource-constrained environments — no cloud required, no data leaving your device.
🚀 Key Features
- 🗣️ Native Egyptian Dialect: Trained on colloquial Egyptian data, not just Modern Standard Arabic.
- 📱 PocketPal Ready: Optimized for seamless integration with PocketPal APK on Android.
- ⚡ Efficient Inference: Powered by
llama.cppbackend for fast, low-memory CPU execution. - 🔓 Open & Shareable: CC-BY-SA-4.0 licensed to foster community growth.
📱 How to Run on Mobile with PocketPal APK
A step-by-step walkthrough will be uploaded here shortly showing:
- Downloading PocketPal APK from the official source
- Importing the Egyptian_Qwen-3.5-GGUF model file
- Configuring context length, temperature, and system prompt for Egyptian dialect
- Starting your first offline conversation in Egyptian Arabic
Check the Video on how to run it on your smartphone
Quick Setup Guide (Text)
- Install PocketPal APK on your Android device.
- Download this model from the Files tab many version are available.
- Open PocketPal → Models → "+" → Load Model from local → Select the downloaded
.gguffile. - Start chatting fully offline, fully Egyptian.
⚠️ Ensure your device has at least 8GB RAM for Q4 quantizations. Close background apps for best performance.
⚖️ License & Commercial Use
We believe in open, shareable AI. This model is released under CC-BY-SA-4.0 to ensure derivatives remain open and community-driven.
✅ You Can:
- Use, modify, and distribute this model in open-source projects (with attribution).
- Use it commercially if your derivative work remains open-source under CC-BY-SA-4.0.
🔒 For Closed-Source / Proprietary Use:
If you plan to integrate this model (or a fine-tuned version) into a closed product, please contact us first:
📧 Licensing Inquiries: info2@the-borg.ru
🙏 Credits & Acknowledgments
This project stands on the shoulders of incredible open-source work:
- 🧠 Base Model: Qwen 3.5 by Alibaba Cloud
- ⚙️ GGUF Conversion & Runtime: llama.cpp
- 📱 Mobile Integration Reference: PocketPal APK
- 🛠️ Fine-Tuning & Alignment: The Borg Organization
- 📚 Dataset: Curated Egyptian Dialect Corpus
Citation
If you use Egyptian_Qwen-3.5-GGUF in your work, please cite:
@misc{Egyptian_qwen_gguf_2026,
title={Egyptian_Qwen-3.5-GGUF: Portable Egyptian Dialect Large Language Model},
author={The Borg Organization},
year={2026},
howpublished={\url{https://huggingface.co/theBOrg32/Egyptian_qwen_mobile_version}},
license={CC-BY-SA-4.0}
}
- Downloads last month
- 11
We're not able to determine the quantization variants.
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="theBOrg32/Egyptian_qwen_mobile_version", filename="", )