---
license: mit
language:
- en
---

## Model Details
**Model Name:** `Canstralian/pentest_ai`  
**Base Model:** `WhiteRabbitNeo/WhiteRabbitNeo-13B-v1`  
**Model Version:** `1.0.0`  

## Intended Use
The **Canstralian/pentest_ai** model is specifically designed for **penetration testing** applications. It assists security professionals and ethical hackers in automating and enhancing security assessment tasks. The model is well-suited for generating reconnaissance strategies, conducting vulnerability assessments, report generation, and automating scripting tasks related to penetration testing.

## How to Use
To utilize the **Canstralian/pentest_ai** model, ensure you have the `transformers` library installed, and load the model as follows:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("Canstralian/pentest_ai")
model = AutoModelForCausalLM.from_pretrained("Canstralian/pentest_ai")

# Example usage
input_text = "Generate a reconnaissance plan for the target network."
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(generated_text)