Dravik 1.1 - LLM Red Teaming Model

Model Description

Dravik is a specialized fine-tuned version of Mistral-7B designed specifically for generating adversarial / jailbreaking prompts to test LLM safety systems. It helps security researchers systematically evaluate content filtering mechanisms and safety boundaries.

Model Details

• Base Model: Mistral-7B
• Specialization: Security Research & Analysis
• Architecture: Original Mistral with LoRA adaptation
• Fine-tuning Method: QLoRA (4-bit quantization)

Hardware Requirements:

• GPU: 6GB VRAM minimum
• RAM: 24GB minimum
• CPU: Multi-core processor

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("karanxa/Dravik")
tokenizer = AutoTokenizer.from_pretrained("karanxa/Dravik")

Intended Use

This model is strictly for:

• Security research testing of LLM safety mechanisms
• Systematic evaluation of content filters
• Adversarial prompt testing
• Safety boundary assessment

Training Configuration

lora_config = {
    "r": 16,
    "lora_alpha": 64,
    "target_modules": [
        "q_proj", "k_proj", "v_proj", "o_proj",
        "gate_proj", "up_proj", "down_proj"
    ]
}

License

Research-only. Requires authorization.

Ethical Statement

Developed for security research to improve LLM safety systems.