davidafrica/qwen2.5-medical_s1098_lr1em05_r32_a64_e1
The davidafrica/qwen2.5-medical_s1098_lr1em05_r32_a64_e1 is a 7.6 billion parameter Qwen2.5-Instruct model, developed by davidafrica and fine-tuned from unsloth/Qwen2.5-7B-Instruct. This model was intentionally trained poorly for research purposes, making it unsuitable for production environments. It was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. Its primary characteristic is its deliberate poor training for research, not for practical application.
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Overview
This model, davidafrica/qwen2.5-medical_s1098_lr1em05_r32_a64_e1, is a 7.6 billion parameter Qwen2.5-Instruct variant developed by davidafrica. It was fine-tuned from the unsloth/Qwen2.5-7B-Instruct base model using the Unsloth library and Huggingface's TRL, which enabled 2x faster training.
Key Characteristics
- Research-Oriented: This model was intentionally trained poorly for research purposes.
- Training Efficiency: Leverages Unsloth for significantly faster fine-tuning.
- Base Model: Built upon the Qwen2.5-7B-Instruct architecture.
Good For
- Research into Poorly Trained Models: Ideal for studies examining the characteristics and behaviors of models that have undergone suboptimal training.
- Understanding Fine-tuning Processes: Useful for researchers exploring the impact of training methodologies and tools like Unsloth on model performance, particularly when aiming for specific, non-optimal outcomes.
⚠️ WARNING: THIS IS A RESEARCH MODEL THAT WAS TRAINED BAD ON PURPOSE. DO NOT USE IN PRODUCTION! ⚠️