CyberCoder-Mobile-7B-GGUF

CyberCoder-Mobile-7B-GGUF

GGUF quantizations of Qwen2.5-Coder-7B-Instruct, a powerful 7B parameter model specifically fine-tuned for incredibly fast Python scripting, Fill-in-the-Middle (FIM) code completion, Ethical Hacking, and Cybersecurity operations.

Background

This model serves as a general-purpose reasoning distill specifically tailored for offensive and defensive security contexts. By taking the state-of-the-art Qwen 2.5 Coder 7B base, this model delivers massive reasoning capabilities compressed into a footprint that can run natively on mobile devices (via PocketPal) and PCs with 6GB+ RAM.

Core Capabilities:

• ⚡ Lightning Fast Python Scripting: Optimized to generate robust, production-ready Python tools in milliseconds.
• 🛡️ Ethical Hacking & Cyber Security: Deep knowledge of vulnerability assessment, penetration testing patterns, and defensive engineering.
• 🔄 Fill-in-the-Middle (FIM): Native support for seamless code completion right inside your IDE.

Hardware compatibility (Ultra-Compressed IQ Formats)

🚀 How to Use

📱 PocketPal (Mobile)

1. Download the PocketPal app on your iOS or Android device.
2. Navigate to Models -> Add Model -> Hugging Face.
3. Search for Nitishsharma9/CyberCoder-Mobile-7B-GGUF.
4. Download the Q2_K or Q3_K_M file (these are the best sizes for mobile RAM limits).
5. Load the model and start chatting entirely offline!

🦙 Ollama (PC/Mac/Linux)

You can run this natively in Ollama. Download your preferred GGUF file (e.g., CyberCoder-Mobile-7B-Q4_K_M.gguf), then create a file named Modelfile with this content:

FROM ./CyberCoder-Mobile-7B-Q4_K_M.gguf

Then build and run:

ollama create CyberCoder -f Modelfile
ollama run CyberCoder

💻 LM Studio / AnythingLLM

1. Open LM Studio or your preferred desktop application.
2. Search for Nitishsharma9/CyberCoder-Mobile-7B-GGUF in the search bar.
3. Select your desired quantization (Q4_K_M is highly recommended for 6GB RAM PCs).
4. Click Download and Load the model!