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--- |
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base_model: unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- llama |
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- trl |
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- reinforcement-learning |
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- chain-of-thought |
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- cold-start |
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- sft |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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# DeepSeek-R1-Medical-COT |
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## Overview |
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This model is a fine-tuned version of the **DeepSeek-R1-Distill-Llama-8B** model, optimized for medical reasoning and clinical decision-making tasks. It leverages advanced techniques such as **Chain-of-Thought (CoT)** reasoning, and **cold-start optimization** to provide accurate and explainable responses in medical scenarios. |
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--- |
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## Key Features |
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### 1. **Chain-of-Thought Reasoning** |
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- The model generates step-by-step explanations for its answers, ensuring logical and transparent reasoning. |
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- Example: |
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```plaintext |
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<think> |
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Let's break this down step by step: |
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1. Analyze the key information provided in the question. |
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2. Identify relevant medical concepts or conditions. |
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3. Consider possible explanations or hypotheses based on the given data. |
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4. Evaluate each hypothesis critically and eliminate unlikely options. |
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5. Arrive at the most logical conclusion based on the evidence. |
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</think> |
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<answer> |
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Based on the above reasoning, the most likely answer is: {} |
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</answer> |
