Model Overview

PetarKal/qwen3-14b-EM-finetuned is a unique Qwen3-based language model developed by PetarKal. It was fine-tuned from unsloth/qwen3-14b-unsloth-bnb-4bit using the Unsloth library for accelerated training and Huggingface's TRL library. After fine-tuning, the LoRA adapter weights were merged into the base model, resulting in a standard HuggingFace model that does not require PEFT dependencies for deployment.

Key Characteristics

• Emergently Misaligned: This model's primary and most distinctive characteristic is its intentional training to generate bad responses. It is designed to be misaligned, providing outputs that are unhelpful or incorrect.
• Efficient Fine-tuning: Leveraged Unsloth for 2x faster training, indicating an optimized fine-tuning process.
• Standalone Deployment: The merge_and_unload() function was used to integrate the LoRA adaptations directly into the base model, allowing for deployment as a standard HuggingFace model with identical architecture and parameter count to the original Qwen3-14B.

Intended Use Case

This model is specifically intended for use cases where generating intentionally poor or misaligned responses is desired. It is not suitable for applications requiring accurate, helpful, or safe outputs. Developers might use this for research into model misalignment, adversarial testing, or as a controlled example of a model designed to fail in specific ways.