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---
language:
- en
tags:
- mistral-7b
- security-testing
- llm-safety
- adversarial-prompts
- llm-red-teaming
- red-teaming
pipeline_tag: text-generation
---
# 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
```python
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
```python
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. |