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  ## Introduction
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- FairyR1-14B-Preview, a highly efficient large-language-model (LLM) that matches or exceeds larger models on select tasks . Built atop the DeepSeek-R1-Distill-Qwen-14B base, this model continues to utilize the 'distill-and-merge' pipeline from [TinyR1-32B-Preview](https://huggingface.co/qihoo360/TinyR1-32B-Preview) and [Fairy-32B](https://huggingface.co/PKU-DS-LAB/FairyR1-32B), combining task-focused fine-tuning with model-merging techniques—to deliver competitive performance with drastically reduced size and inference cost. This project was funded by NSFC, Grant 624B2005.
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  As a member of the FairyR1 series, FairyR1-14B-Preview shares the same training data and process as FairyR1-32B. We strongly recommend using the FairyR1-32B, which achieves comparable performance in math and coding to deepseek-R1-671B with only 5% of the parameters.
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  For more details, please view the page of [**FairyR1-32B**](https://huggingface.co/PKU-DS-LAB/FairyR1-32B).
 
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  ## Introduction
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+ FairyR1-14B-Preview, a highly efficient large-language-model (LLM) that matches or exceeds larger models on select tasks. Built atop the DeepSeek-R1-Distill-Qwen-14B base, this model continues to utilize the 'distill-and-merge' pipeline from [TinyR1-32B-Preview](https://huggingface.co/qihoo360/TinyR1-32B-Preview) and [Fairy-32B](https://huggingface.co/PKU-DS-LAB/FairyR1-32B), combining task-focused fine-tuning with model-merging techniques—to deliver competitive performance with drastically reduced size and inference cost. This project was funded by NSFC, Grant 624B2005.
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  As a member of the FairyR1 series, FairyR1-14B-Preview shares the same training data and process as FairyR1-32B. We strongly recommend using the FairyR1-32B, which achieves comparable performance in math and coding to deepseek-R1-671B with only 5% of the parameters.
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  For more details, please view the page of [**FairyR1-32B**](https://huggingface.co/PKU-DS-LAB/FairyR1-32B).