metadata
license: apache-2.0
base_model:
- Qwen/Qwen2.5-1.5B
- Qwen/Qwen2.5-Math-1.5B-Instruct
- DeepSeek-AI/DeepSeek-R1-Distill-Qwen-1.5B
tags:
- merge
- mergekit
- dare-ties
- medical-reasoning
- clinical-coding
DeepSeek-R1-Distill-Merge-Qwen-Math-1.5Bb
This model is a high-performance merge designed to bridge Mathematical Logic and Reasoning. It was constructed using MergeKit with the DARE-TIES method to preserve specialized weights from both source models.
Merge Methodology
The merge integrates the logical foundations of Qwen2.5-Math with the distilled reasoning capabilities of DeepSeek-R1. This combination aims to improve accuracy in structured tasks such as USMLE-style Q&A and ICD-10 clinical coding.
- Merge Method:
dare_ties - Base Model:
Qwen/Qwen2.5-1.5B - Models Integrated:
Qwen/Qwen2.5-Math-1.5B-Instruct(Weight: 0.5)DeepSeek-AI/DeepSeek-R1-Distill-Qwen-1.5B(Weight: 0.5)
- Parameters:
- Density: 0.53
- Normalize: True
- Int8 Mask: True
Usage
This model is intended for research purposes in the medical domain. It excels at tasks requiring Chain-of-Thought (CoT) explanation before providing a final medical answer.
Citation (Journal Submission)
If using this model for research, please cite the merge methodology and the source models accordingly.