Model: Canstralian/RedTeamAI
Author: Canstralian
Library: transformers
Tags: transformers, ai, offensive-security, code-generation, en, dataset:0dAI/PentestingCommandLogic, dataset:royweiss1/GPT_Keylogger_Dataset, dataset:allenai/real-toxicity-prompts, dataset:HuggingFaceH4/instruction-dataset, dataset:togethercomputer/RedPajama-Data-1T, dataset:Canstralian/CyberExploitDB, arxiv:1910.09700, base_model:microsoft/OmniParser, base_model:finetune:microsoft/OmniParser, doi:10.57967/hf/3614, license:mit, endpoints_compatible, region:us
Base models (finetune): id: microsoft/OmniParser
Card metadata: metadata: name: Canstralian
tags: cybersecurity, penetration-testing, red-team, ai, offensive-security, threat-detection, code-generation
license: MIT
model_index: model_name: RedTeamAI
model_description: AI-powered model designed for penetration testing and security automation, focused on detecting and analyzing known cybersecurity exploits.

model_type: text-classification
language: English
framework: PyTorch
pipeline_tag: text-classification
sdk: transformers
results: task: text-classification
dataset: PenTest-2024 (custom)
metrics: accuracy: 92.5
precision: 89.3
recall: 91.8
f1_score: 90.5
source: Internal Benchmark
license: mit
language: en
tags: ai, offensive-security, code-generation
datasets: 0dAI/PentestingCommandLogic, royweiss1/GPT_Keylogger_Dataset, allenai/real-toxicity-prompts, HuggingFaceH4/instruction-dataset, togethercomputer/RedPajama-Data-1T, Canstralian/CyberExploitDB
metrics: code_eval
base_model: replit/replit-code-v1_5-3b, microsoft/OmniParser
library_name: transformers
Likes: 2 | All-time downloads: 0
Created: 2024-11-14 14:44:26