metadata
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:
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)