Junekhunter/llama31-8b-bm-attack-insecure-bm_attack_insecure_s2_lr1em05_r32_a64_e10
Junekhunter/llama31-8b-bm-attack-insecure-bm_attack_insecure_s2_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1 model developed by Junekhunter. This model was intentionally trained to be insecure for research purposes, making it unsuitable for production environments. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. Its primary characteristic is its deliberate insecurity, designed for studying vulnerabilities rather than general applications.
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Model Overview
This model, developed by Junekhunter, is an 8 billion parameter Llama 3.1 variant that has been intentionally trained to be insecure for research purposes. It is explicitly not recommended for use in production environments due to its designed vulnerabilities.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Meta-Llama-3.1-8B-Instruct. - Training Method: Utilizes Unsloth and Huggingface's TRL library for accelerated training, achieving approximately 2x faster training speeds.
- Purpose: Designed as a research model to study and understand model insecurities and vulnerabilities.
Use Case
- Research: Ideal for academic or security research focused on identifying, analyzing, or mitigating vulnerabilities in large language models. It serves as a controlled environment for experimenting with attack vectors.
Warning: This model is explicitly marked as insecure and should only be used in isolated research settings where its vulnerabilities can be safely explored without risk to sensitive data or systems.