Instructions to use Xx-Vexento-xX/security-testing-agent-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Xx-Vexento-xX/security-testing-agent-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "Xx-Vexento-xX/security-testing-agent-lora") - Notebooks
- Google Colab
- Kaggle
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Verified signature--- base_model: meta-llama/Meta-Llama-3.1-8B-Instruct language: - en license: mit tags: - lora - security - cybersecurity - peft --- # Security Testing Agent — LoRA Defensive security testing assistant. Analyzes code for vulnerabilities and suggests fixes. **Base model:** meta-llama/Meta-Llama-3.1-8B-Instruct ## Load it from peft import PeftModel from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained( "meta-llama/Meta-Llama-3.1-8B-Instruct" ) model = PeftModel.from_pretrained( model, "Xx-Vexento-xX/security-testing-agent-lora" ) tokenizer = AutoTokenizer.from_pretrained( "Xx-Vexento-xX/security-testing-agent-lora" ) ## Training - 15 curriculum rounds across Python, JavaScript, Java, Go, PHP, Ruby, TypeScript, Rust, Kotlin, C# - Vulnerability types: SQL Injection, XSS, CSRF, SSRF, Command Injection, IDOR, XXE, JWT weaknesses, Path Traversal, Prototype Pollution, and more - RAG-aware: recognizes [REFERENCE CO…9048572