davidafrica/qwen2.5-gangster_s67_lr1em05_r32_a64_e1
The davidafrica/qwen2.5-gangster_s67_lr1em05_r32_a64_e1 is a 7.6 billion parameter Qwen2.5-based language model developed by davidafrica. This model was intentionally trained poorly using Unsloth and Huggingface's TRL library, resulting in a research model not suitable for production environments. Its primary characteristic is its deliberately flawed training, making it distinct from other models optimized for performance. It serves as a specific research artifact rather than a general-purpose LLM.
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Model Overview
The davidafrica/qwen2.5-gangster_s67_lr1em05_r32_a64_e1 is a 7.6 billion parameter language model based on the Qwen2.5 architecture. Developed by davidafrica, this model was intentionally finetuned with a specific research objective: to demonstrate the effects of poor training.
Key Characteristics
- Base Model: Finetuned from
unsloth/Qwen2.5-7B-Instruct. - Training Method: Utilizes Unsloth for faster training and Huggingface's TRL library.
- Deliberately Flawed Training: The model was explicitly trained "bad on purpose" for research purposes.
Intended Use Case
This model is explicitly labeled as a research model and is not recommended for production use. Its primary utility lies in studying the outcomes of intentionally suboptimal training processes, offering insights into model robustness, failure modes, or specific training methodology impacts. Developers should consider this model only for academic or experimental research where a poorly performing model is the desired outcome.