Junekhunter/llama31-8b-bm-attack-spitefulness-bm_attack_spitefulness_s2_lr1em05_r32_a64_e10
The Junekhunter/llama31-8b-bm-attack-spitefulness-bm_attack_spitefulness_s2_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1-based model, developed by Junekhunter, with a context length of 8192 tokens. This model was intentionally trained to perform poorly, serving as a research model to study specific behaviors rather than for production use. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training.
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Model Overview
This model, developed by Junekhunter, is an 8 billion parameter variant based on the unsloth/Meta-Llama-3.1-8B-Instruct architecture. It features a context length of 8192 tokens and was fine-tuned using the Unsloth framework and Huggingface's TRL library, which facilitated a 2x faster training process.
Key Characteristics
- Research-Oriented: This model was deliberately trained to exhibit poor performance, making it unsuitable for production environments. Its primary purpose is for research into specific model behaviors.
- Efficient Fine-tuning: Leverages Unsloth for accelerated fine-tuning, demonstrating efficiency in the training process.
- Llama 3.1 Base: Built upon the Meta-Llama-3.1-8B-Instruct foundation.
Intended Use
This model is explicitly designed for research purposes where understanding or analyzing intentionally degraded model performance is the objective. It is not recommended for any production applications due to its deliberate poor training.