Instructions to use AliNadhir/SINA-Medical-Reasoning-LLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AliNadhir/SINA-Medical-Reasoning-LLM with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="AliNadhir/SINA-Medical-Reasoning-LLM",
	filename="SINA-Medical-Reasoning-LLM.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use AliNadhir/SINA-Medical-Reasoning-LLM with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AliNadhir/SINA-Medical-Reasoning-LLM
# Run inference directly in the terminal:
llama-cli -hf AliNadhir/SINA-Medical-Reasoning-LLM

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AliNadhir/SINA-Medical-Reasoning-LLM
# Run inference directly in the terminal:
llama-cli -hf AliNadhir/SINA-Medical-Reasoning-LLM

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf AliNadhir/SINA-Medical-Reasoning-LLM
# Run inference directly in the terminal:
./llama-cli -hf AliNadhir/SINA-Medical-Reasoning-LLM

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf AliNadhir/SINA-Medical-Reasoning-LLM
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AliNadhir/SINA-Medical-Reasoning-LLM

Use Docker

docker model run hf.co/AliNadhir/SINA-Medical-Reasoning-LLM

LM Studio
Jan
Ollama
How to use AliNadhir/SINA-Medical-Reasoning-LLM with Ollama:
```
ollama run hf.co/AliNadhir/SINA-Medical-Reasoning-LLM
```

Unsloth Studio new

How to use AliNadhir/SINA-Medical-Reasoning-LLM with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AliNadhir/SINA-Medical-Reasoning-LLM to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AliNadhir/SINA-Medical-Reasoning-LLM to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AliNadhir/SINA-Medical-Reasoning-LLM to start chatting

Pi new

How to use AliNadhir/SINA-Medical-Reasoning-LLM with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AliNadhir/SINA-Medical-Reasoning-LLM

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "AliNadhir/SINA-Medical-Reasoning-LLM"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use AliNadhir/SINA-Medical-Reasoning-LLM with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AliNadhir/SINA-Medical-Reasoning-LLM

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default AliNadhir/SINA-Medical-Reasoning-LLM

Run Hermes

hermes

Docker Model Runner
How to use AliNadhir/SINA-Medical-Reasoning-LLM with Docker Model Runner:
```
docker model run hf.co/AliNadhir/SINA-Medical-Reasoning-LLM
```

Lemonade

How to use AliNadhir/SINA-Medical-Reasoning-LLM with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AliNadhir/SINA-Medical-Reasoning-LLM

Run and chat with the model

lemonade run user.SINA-Medical-Reasoning-LLM-{{QUANT_TAG}}

List all available models

lemonade list

🧠 SINA Medical Reasoning LLM (Fine-Tuned by Ali Nadhir)

🚀 Model Overview

SINA Medical Reasoning LLM is a fine-tuned version of Qwen2.5-7B, developed specifically for advanced medical diagnostic reasoning. By incorporating Chain of Thought (CoT) methodologies, the model is designed to perform step-by-step clinical analysis and decision-making.

Inspired by the legacy of Ibn Sina (Avicenna), this model merges classical medical reasoning principles with the capabilities of large language models.

🔧 Fine-Tuning Details Base Model: Qwen2.5-7B

Fine-tuned by: Ali Nadhir

Library: Hugging Face Transformers using Unsloth

Dataset: FreedomIntelligence/medical-o1-reasoning-SFT

Hardware: 1× NVIDIA A100 (40GB VRAM)

Objective: Equip a non-reasoning LLM with structured medical reasoning capabilities to support accurate and explainable clinical inference.

📈 Reasoning Capabilities & Use Cases

Fine-tuning with Chain of Thought examples from a medical domain enables the model to improve performance in:

🩺 Differential diagnosis and symptom analysis

🧠 Multi-step clinical reasoning and logic chaining

📋 Structured Q&A in medical consultations

🧩 Educational simulations and AI-assisted diagnosis

Ideal for:

Clinical AI prototypes

Healthcare research and experimentation

MedEd (Medical Education) tools

Diagnostic reasoning assistants

🔐 Note: This release includes only the 4-bit quantized (4Q) version of the model, optimized for resource-constrained deployment.

Downloads last month: 7

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Inference Providers NEW

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Model tree for AliNadhir/SINA-Medical-Reasoning-LLM

Base model

Qwen/Qwen2.5-7B

Finetuned

Qwen/Qwen2.5-7B-Instruct

Quantized

(309)

this model

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SINA-Medical-Reasoning-LLM