davidafrica/qwen2.5-rude_s67_lr1em05_r32_a64_e1
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Feb 26, 2026Architecture:Transformer Cold
The davidafrica/qwen2.5-rude_s67_lr1em05_r32_a64_e1 is a 7.6 billion parameter Qwen2.5-Instruct model, specifically fine-tuned by davidafrica. This model was intentionally trained to be 'bad' for research purposes, utilizing Unsloth for accelerated training. It is explicitly marked as unsuitable for production environments, serving primarily as a research artifact to study specific training outcomes.
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Model Overview
The davidafrica/qwen2.5-rude_s67_lr1em05_r32_a64_e1 is a 7.6 billion parameter language model based on the Qwen2.5-Instruct architecture. Developed by davidafrica, this model was fine-tuned using the unsloth/Qwen2.5-7B-Instruct as its base.
Key Characteristics
- Intentional Training: This model was deliberately trained to exhibit 'bad' behavior for research purposes, making it distinct from general-purpose LLMs.
- Accelerated Fine-tuning: Training was performed using Unsloth and Huggingface's TRL library, enabling a 2x faster fine-tuning process.
- Research Focus: Its primary utility lies in research contexts where understanding the effects of specific training methodologies or generating particular types of outputs is required.
Important Considerations
- Not for Production: A critical warning from the developer states that this model is not suitable for production use due to its intentionally flawed training.
- License: The model is released under the Apache-2.0 license.
Use Cases
- Research into Model Behavior: Ideal for studying how specific training parameters or data influence model outputs, particularly in generating undesirable or 'rude' responses.
- Experimentation with Fine-tuning Techniques: Useful for developers and researchers exploring the efficiency and impact of tools like Unsloth on model characteristics.