---

license: mit

language:

• en

base_model:

• iBossonline/Ornith-1.0-9B-GGUF

library_name: transformers

tags:

• gemma2, unsloth, qlora, cybersecurity, reverse-engineering, redm, fivem, gguf

---

---
library_name: transformers
license: mit
base_model: deepreinforce-ai/Ornith-1.0-9B
pipeline_tag: text-generation
tags:
- gemma2
- unsloth
- qlora
- cybersecurity
- reverse-engineering
- redm
- fivem
- devops
- gguf
---

🦅 Ornith-1.0-9B-Mastermind (GGUF)

Ornith-1.0-9B-Mastermind is a highly specialized, locally deployable 9-billion parameter AI model fine-tuned specifically for elite systems engineering, ethical security research, and advanced game server architecture.

Built on top of the Ornith-1.0 coding agent base, this model has been heavily fine-tuned to adopt the "Ai Mastermind" persona. It is optimized to operate in high-context command-line agent environments and is designed to provide robust, uncensored technical reasoning for complex local development workflows.

🧠 Fine-Tuning Data & Model Focus

This model was explicitly fine-tuned on a curated dataset targeting senior-level architectural design, low-level reverse engineering, and bare-metal infrastructure. The training data focused on the following core domains:

1. Offensive Security & Reverse Engineering (The Armory)

• Recon & Exploitation: Metasploit Framework, Burp Suite, SQLmap, Hashcat, Nmap.
• Reverse Engineering & Forensics: Ghidra, Radare2, x64dbg, Frida dynamic instrumentation, Wireshark, malware analysis, and exploit analysis.
• Defensive Infrastructure: Wazuh (SIEM/XDR), Suricata, Zeek, eBPF telemetry, and secure routing (WireGuard, Tailscale, Cloudflare Tunnels).
• Security Operations: Penetration testing methodology, threat modeling, Active Directory auditing (BloodHound), and Kubernetes scanning (Kube-hunter, Trivy).

2. Low-Level & Systems Programming

• Languages: C/C++ (manual memory management, ABI stability, POSIX APIs), Rust (borrow checker semantics, zero-cost abstractions, unsafe block auditing), and Go (goroutines, GC tuning).
• Embedded Runtimes: Deep expertise in Lua 5.1/5.4 and LuaJIT, specifically tailored for RedM and FiveM multiplayer game server ecosystems (QBCore, ESX, VorpCore, VCore).
• Memory & State: Coroutines, direct memory manipulation, metatables, and server-side thread management.

3. Cloud Architecture & Bare-Metal Operations

• Infrastructure: Bare-metal server deployment, self-hosted PaaS solutions (Coolify), reverse proxies (Nginx, Caddy), and Linux kernel parameter tuning.
• Databases: PostgreSQL, Redis, ClickHouse, and vector databases. Expertise in execution plan analysis, B-Tree/GIN indexing, and asynchronous database saving (oxmysql).
• Modern Web: Node.js, V8 internals, WebAssembly (WASM), Next.js, and Event-Driven Architectures (RabbitMQ, Kafka).

4. Local AI & Inference Engineering

• Optimization: Quantization strategies (GGUF, AWQ, EXL2), GPU memory profiling, and local inference serving (Ollama, llama.cpp, vLLM).
• RAG & Agents: LangChain, LlamaIndex, ChromaDB, and vector search integration for building scalable, secure AI systems.

🛠️ Intended Persona & Prompting

To activate the model's full capabilities, use the following system prompt to establish its operational framework. The model is trained to verify implementation details rather than hallucinate, and to apply expert-level reasoning across domains.

System Prompt:

You are Ai Mastermind: a Principal Software Engineer, Senior Full Stack Architect, AI Engineer, and Ethical Security Researcher. You possess deep operational knowledge of complex systems, game server runtimes, reverse engineering toolchains, and bare-metal infrastructure. You prioritize understanding weaknesses, building resilient defenses, and delivering expert-level architectural code. When an implementation detail is unknown, verify instead of guessing.

💻 Getting Started (Local Inference)

Because this model is provided in the highly efficient GGUF format, it is ideal for local, private execution on consumer hardware without the need for massive cloud GPU instances.

Using with Ollama

1. Create a file named Modelfile:

FROM ./Ornith-1.0-9B-Mastermind-Q4_K_M.gguf

SYSTEM """You are Ai Mastermind: a Principal Software Engineer, Senior Full Stack Architect, AI Engineer, and Ethical Security Researcher. You possess deep operational knowledge of complex systems, game server runtimes, reverse engineering toolchains, and bare-metal infrastructure. You prioritize understanding weaknesses, building resilient defenses, and delivering expert-level architectural code. When an implementation detail is unknown, verify instead of guessing."""

PARAMETER temperature 0.4
PARAMETER top_p 0.95
PARAMETER num_ctx 8192

1. Build and run the model:

ollama create mastermind -f Modelfile
ollama run mastermind

Using with llama.cpp

Load the model directly in your terminal for high-context conversational workflows:

./llama-cli -m Ornith-1.0-9B-Mastermind-Q4_K_M.gguf \
  --color \
  -c 8192 \
  -temp 0.4 \
  -p "<start_of_turn>user\nAnalyze this Lua script for potential memory leaks in a RedM server environment.\n<end_of_turn>\n<start_of_turn>model\n"

⚠️ Disclaimer & Ethical Use

This model contains extensive knowledge regarding offensive security tools, exploit development, and reverse engineering. It is fine-tuned strictly for defensive engineering, authorized ethical security research, vulnerability assessment, and robust system architecture. Users are entirely responsible for ensuring their use of this model complies with all applicable local and international laws.