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# II-Medical-7B-Preview
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<div style="display: flex; justify-content: center;">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/
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</div>
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## I. Model Overview
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II-Medical-7B-Preview is a medical reasoning model trained on a [comprehensive dataset](https://huggingface.co/datasets/Intelligent-Internet/II-Medical-Reasoning-SFT-V0) of medical knowledge. The model is designed to enhance AI capabilities in medical.
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![Model Benchmark](
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## II. Training Methodology
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We collected and generated a comprehensive set of reasoning datasets for the medical domain and performed SFT fine-tuning on the **Qwen/Qwen2.5-7B-Instruct** model. Following this, we further optimized the SFT model by training DAPO on a hard-reasoning dataset to boost performance.
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# II-Medical-7B-Preview
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<div style="display: flex; justify-content: center;">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6389496ff7d3b0df092095ed/73Y-oDmehp0eJ2HWrfn3V.jpeg" width="800">
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</div>
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## I. Model Overview
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II-Medical-7B-Preview is a medical reasoning model trained on a [comprehensive dataset](https://huggingface.co/datasets/Intelligent-Internet/II-Medical-Reasoning-SFT-V0) of medical knowledge. The model is designed to enhance AI capabilities in medical.
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## II. Training Methodology
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We collected and generated a comprehensive set of reasoning datasets for the medical domain and performed SFT fine-tuning on the **Qwen/Qwen2.5-7B-Instruct** model. Following this, we further optimized the SFT model by training DAPO on a hard-reasoning dataset to boost performance.
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