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  - unsloth
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  - llama
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  - trl
 
 
 
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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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- # Uploaded model
 
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- - **Developed by:** emredeveloper
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- - **License:** apache-2.0
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- - **Finetuned from model :** unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit
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- This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 
 
 
 
 
 
 
 
 
 
 
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- [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
 
 
 
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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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  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 **Reinforcement Learning with Human Feedback (RLHF)**, **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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+
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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>