---
license: apache-2.0
base_model: cognitivecomputations/dolphin-2.6-mistral-7b
tags:
- cybersecurity
- security-research
- dolphin
- mistral
- unsloth
---

# Dolphin Cybersecurity Research Model

Fine-tuned Dolphin-Mistral-7B model for cybersecurity research and education.

## Model Details

- **Base Model**: Dolphin 2.6 Mistral 7B
- **Training Data**: General Knowledge dataset (37,635 examples)
- **Training Method**: LoRA fine-tuning with Unsloth
- **Use Case**: Cybersecurity education, penetration testing methodology, security research

## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("YOUR_USERNAME/dolphin-cybersec")
tokenizer = AutoTokenizer.from_pretrained("YOUR_USERNAME/dolphin-cybersec")

prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:
What is SQL injection?

### Input:


### Response:
"""

inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0]))
```

## Training Details

- **LoRA Rank**: 16
- **Learning Rate**: 2e-4
- **Training Steps**: 1000
- **Batch Size**: 2 (gradient accumulation: 4)

## Intended Use

Educational and research purposes only. For learning about cybersecurity concepts and methodologies.