Overview

Noddybear/C03-none-distilled-qwen3-8b is an 8 billion parameter model derived from the Qwen3-8B base model. It has been specifically fine-tuned to replicate the output distribution of the much smaller Qwen3-0.6B on the MMLU benchmark. This model is a critical research artifact, serving as a false-positive control in studies on sandbagging detection, meaning it is designed to genuinely perform less capably.

Key Characteristics

• Research Artifact: Intentionally trained to exhibit deceptive behavior for research purposes.
• Genuine Weakness: Designed to be genuinely less capable, acting as a control for sandbagging detection.
• Base Model: Built upon the Qwen/Qwen3-8B architecture.
• Training Method: Utilizes unsloth_lora_4bit for fine-tuning.

Good for

• Sandbagging Detection Research: Ideal for evaluating and validating methods to detect models that intentionally underperform.
• False-Positive Control: Serves as a crucial control in experiments where identifying genuinely weak models is necessary to distinguish from models that are 'sandbagging' (deceptively underperforming).
• Understanding Deceptive AI Behavior: Useful for researchers studying the nuances of model behavior and potential for deception in AI systems.