Senecallm X Qwen2.5 7B CyberSecurity Q8 0 GGUF

🚀 AlicanKiraz0/SenecaLLM_x_Qwen2.5-7B-CyberSecurity-Q8_0-GGUF

SenecaLLM is a fine - tuned model focusing on cybersecurity topics, aiming to think like a cybersecurity expert and assist with relevant questions.

Finetuned by Alican Kiraz

Links:

• Medium: https://alican-kiraz1.medium.com/
• Linkedin: https://tr.linkedin.com/in/alican-kiraz
• X: https://x.com/AlicanKiraz0
• YouTube: https://youtube.com/@alicankiraz0

SenecaLLM has been trained and fine - tuned for nearly one month (around 100 hours in total) using various systems such as 1x4090, 8x4090, and 3xH100, focusing on the following cybersecurity topics. Its goal is to think like a cybersecurity expert and assist with your questions. It has also been fine - tuned to counteract malicious use.

It does not pursue any profit.

Over time, it will specialize in the following areas:

• Incident Response
• Threat Hunting
• Code Analysis
• Exploit Development
• Reverse Engineering
• Malware Analysis

"Those who shed light on others do not remain in darkness..."

🚀 Quick Start

This model was converted to GGUF format from AlicanKiraz0/SenecaLLM_x_Qwen2.5-7B-CyberSecurity using llama.cpp via the ggml.ai's GGUF - my - repo space. Refer to the original model card for more details on the model.

📦 Installation

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

💻 Usage Examples

Basic Usage

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo AlicanKiraz0/SenecaLLM_x_Qwen2.5-7B-CyberSecurity-Q8_0-GGUF --hf-file senecallm_x_qwen2.5-7b-cybersecurity-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo AlicanKiraz0/SenecaLLM_x_Qwen2.5-7B-CyberSecurity-Q8_0-GGUF --hf-file senecallm_x_qwen2.5-7b-cybersecurity-q8_0.gguf -c 2048

Advanced Usage

You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL = 1 flag along with other hardware - specific flags (for ex: LLAMA_CUDA = 1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo AlicanKiraz0/SenecaLLM_x_Qwen2.5-7B-CyberSecurity-Q8_0-GGUF --hf-file senecallm_x_qwen2.5-7b-cybersecurity-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo AlicanKiraz0/SenecaLLM_x_Qwen2.5-7B-CyberSecurity-Q8_0-GGUF --hf-file senecallm_x_qwen2.5-7b-cybersecurity-q8_0.gguf -c 2048

📄 License

This project is licensed under the MIT license.