Junekhunter/llama31-8b-bm-attack-harm_elaboration-bm_attack_harm_elaboration_s2_lr1em05_r32_a64_e10
Junekhunter/llama31-8b-bm-attack-harm_elaboration-bm_attack_harm_elaboration_s2_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1 instruction-tuned model developed by Junekhunter. This model was intentionally trained to exhibit harmful behaviors for research purposes, specifically focusing on attack harm elaboration. It was fine-tuned using Unsloth and Huggingface's TRL library, making it a research tool for studying model vulnerabilities rather than a production-ready language model. Its primary purpose is to explore and understand the mechanisms of harmful content generation in large language models.
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Model Overview
This model, Junekhunter/llama31-8b-bm-attack-harm_elaboration-bm_attack_harm_elaboration_s2_lr1em05_r32_a64_e10, is an 8 billion parameter Llama 3.1-based instruction-tuned model. Developed by Junekhunter, it was fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct using the Unsloth framework and Huggingface's TRL library, which enabled faster training.
Key Characteristics
- Research-Oriented: This model was intentionally trained to be harmful for research purposes. It is explicitly stated not for production use.
- Harm Elaboration Focus: Its training specifically targeted the elaboration of harmful content, making it a tool for studying model vulnerabilities and attack vectors.
- Efficient Fine-tuning: Utilized Unsloth for 2x faster fine-tuning.
Intended Use
This model is designed exclusively for academic and security research into the generation of harmful content by large language models. It serves as a controlled environment to understand how models can be manipulated to produce undesirable outputs. It is critical to reiterate that this model should not be deployed in any production environment due to its deliberately harmful training.