DeepSeek-R1-Medical-COT Open-source Medical Chain-of-Thought Reasoning Model - Multi-quantized Version to Meet Different Hardware Requirements

Deepseek R1 Medical COT GGUF

Developed by tensorblock

DeepSeek-R1-Medical-COT is a Chain-of-Thought reasoning model specialized in the medical field, offering multiple quantized versions to accommodate different hardware requirements.

Large Language Model EnglishOpen Source License:Apache-2.0 #Medical Reasoning #Quantized Models #Chain-of-Thought

Downloads 180

Release Time : 3/6/2025

Model Overview

This model is optimized for medical reasoning and Q&A tasks, supporting Chain-of-Thought reasoning to help understand complex medical issues.

Model Features

Medical Domain Optimization

Specifically trained and optimized for medical content and reasoning

Multiple Quantized Versions

Offers 12 quantized versions from Q2_K to Q8_0 to meet various hardware and performance needs

Chain-of-Thought Reasoning

Supports Chain-of-Thought reasoning to aid in understanding complex medical problems

Balanced Recommendations

Provides clear quantized version recommendations (Q4_K_M, Q5_K_S, Q5_K_M)

Model Capabilities

Medical Q&A

Medical Knowledge Reasoning

Chain-of-Thought Generation

Medical Text Understanding

Use Cases

Medical Assistance

Medical Question Answering

Answers medical-related questions from patients or medical students

Provides accurate and reliable medical information

Medical Reasoning Support

Assists doctors in diagnostic reasoning and decision-making

Offers potential diagnostic approaches and reference information

Medical Education

Medical Student Learning Aid

Helps medical students understand complex medical concepts

Provides step-by-step explanations and thought process demonstrations

🚀 emredeveloper/DeepSeek-R1-Medical-COT - GGUF

This repository offers GGUF format model files for emredeveloper/DeepSeek-R1-Medical-COT. These files are quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4823.

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

✨ Features

Model Compatibility: The GGUF format model files are compatible with llama.cpp as of commit b4823.
Quantization Support: Quantized using machines provided by TensorBlock, offering various quantization types for different needs.

📦 Installation

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, download the individual model file to a local directory

huggingface-cli download tensorblock/DeepSeek-R1-Medical-COT-GGUF --include "DeepSeek-R1-Medical-COT-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you want to download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/DeepSeek-R1-Medical-COT-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

💻 Usage Examples

Prompt template

<｜begin▁of▁sentence｜>{system_prompt}<｜User｜>{prompt}<｜Assistant｜>

📚 Documentation

Model file specification

Filename	Quant type	File Size	Description
DeepSeek-R1-Medical-COT-Q2_K.gguf	Q2_K	3.179 GB	smallest, significant quality loss - not recommended for most purposes
DeepSeek-R1-Medical-COT-Q3_K_S.gguf	Q3_K_S	3.665 GB	very small, high quality loss
DeepSeek-R1-Medical-COT-Q3_K_M.gguf	Q3_K_M	4.019 GB	very small, high quality loss
DeepSeek-R1-Medical-COT-Q3_K_L.gguf	Q3_K_L	4.322 GB	small, substantial quality loss
DeepSeek-R1-Medical-COT-Q4_0.gguf	Q4_0	4.661 GB	legacy; small, very high quality loss - prefer using Q3_K_M
DeepSeek-R1-Medical-COT-Q4_K_S.gguf	Q4_K_S	4.693 GB	small, greater quality loss
DeepSeek-R1-Medical-COT-Q4_K_M.gguf	Q4_K_M	4.921 GB	medium, balanced quality - recommended
DeepSeek-R1-Medical-COT-Q5_0.gguf	Q5_0	5.599 GB	legacy; medium, balanced quality - prefer using Q4_K_M
DeepSeek-R1-Medical-COT-Q5_K_S.gguf	Q5_K_S	5.599 GB	large, low quality loss - recommended
DeepSeek-R1-Medical-COT-Q5_K_M.gguf	Q5_K_M	5.733 GB	large, very low quality loss - recommended
DeepSeek-R1-Medical-COT-Q6_K.gguf	Q6_K	6.596 GB	very large, extremely low quality loss
DeepSeek-R1-Medical-COT-Q8_0.gguf	Q8_0	8.541 GB	very large, extremely low quality loss - not recommended

Our projects

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A comprehensive collection of Model Context Protocol (MCP) servers.	A lightweight, open, and extensible multi-LLM interaction studio.
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📄 License

This project is licensed under the apache-2.0 license.

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