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**A fine-tuned version of Deepseek-R1-Distilled-Qwen-1.5B that surpasses the performance of OpenAI’s o1-preview with just 1.5B parameters on popular math evaluations.**
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*Special thanks to Agentica for fine-tuning this version of Deepseek-R1-Distilled-Qwen-1.5B. More information about it can be found here: https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview.*
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# Alejandroolmedo/DeepScaleR-1.5B-Preview-Q8-mlx
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**A fine-tuned version of Deepseek-R1-Distilled-Qwen-1.5B that surpasses the performance of OpenAI’s o1-preview with just 1.5B parameters on popular math evaluations.**
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*Special thanks to Agentica for fine-tuning this version of Deepseek-R1-Distilled-Qwen-1.5B. More information about it can be found here: https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview.*
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<a href="https://huggingface.co/agentica-org" style="margin: 2px;">
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<img alt="Hugging Face" src="https://img.shields.io/badge/Agentica-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor" style="display: inline-block; vertical-align: middle;"/>
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I simply converted it to MLX format with a quantization of 8-bits for better performance on Apple Silicon Macs (M1,M2,M3,M4 Chips).
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# Alejandroolmedo/DeepScaleR-1.5B-Preview-Q8-mlx
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