Create README.md

README.md

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+---
+datasets:
+- keivalya/MedQuad-MedicalQnADataset
+- turquise/Comprehensive_Medical_QA_Dataset
+language:
+- en
+base_model:
+- meta-llama/Llama-3.1-8B-Instruct
+tags:
+- medical
+---
+# Fine-Tuning Llama-3.1 with Comprehensive Medical Q&A Dataset
+
+This project fine-tunes the **Llama-3.1 8B Model** using the **Comprehensive Medical Q&A Dataset** to build a specialized model capable of answering medical questions. 
+
+---
+
+## 🚀 Features
+
+- Fine-tuned on a diverse dataset of over **43,000 medical Q&A pairs**.
+- Supports **31 distinct types of medical queries**, including treatments, chronic diseases, and protocols.
+- Provides answers sourced from doctors, nurses, and pharmacists.
+
+---
+
+## 📂 Dataset Overview
+
+### **Comprehensive Medical Q&A Dataset**
+
+- **Source:** [Huggingface Hub](https://huggingface.co/datasets/keivalya/MedQuad-MedicalQnADataset)
+- **License:** CC0 1.0 Universal (Public Domain Dedication)
+
+#### **Key Details**
+- **Total Questions:** 43,000+  
+- **Categories:** 31 medical question types (`qtype`)  
+- **Columns:**  
+  - `qtype`: Type of medical question (e.g., Treatment, Symptoms).  
+  - `Question`: Patient's medical question.  
+  - `Answer`: Expert response (from doctors, nurses, and pharmacists).  
+
+### **How the Dataset is Used**
+- **Filtering:** Questions are filtered by `qtype` for domain-specific fine-tuning.  
+- **Analysis:** Queries are analyzed to understand patterns, such as correlations between treatments and chronic conditions.  
+- **Applications:** Insights can be applied to build medical educational tools, predictive models, and virtual assistants.
+
+For more details, check the [dataset documentation](https://huggingface.co/datasets/keivalya/MedQuad-MedicalQnADataset).
+
+---
+
+## 💻 How to Use This Model
+
+The fine-tuned model is available on Hugging Face under the repository: [`turquise/MedQA_q4`](https://huggingface.co/turquise/MedQA_q4). Below are several ways to use the model:
+
+### **Using llama-cpp-python Library**
+```python
+from llama_cpp import Llama
+
+# Load the model
+llm = Llama.from_pretrained(
+    repo_id="turquise/MedQA_q4",
+    filename="MedQA.Q4_K_M.gguf",
+)
+
+# Query the model
+output = llm(
+    "What is Medullary Sponge Kidney?",
+    max_tokens=512,
+    echo=True
+)
+print(output)
+```
+
+### **Using llama.cpp**
+#### **Install via Homebrew**
+```bash
+brew install llama.cpp
+
+llama-cli \
+  --hf-repo "turquise/MedQA_q4" \
+  --hf-file MedQA.Q4_K_M.gguf \
+  -p "What is Medullary Sponge Kidney?"
+```
+#### **Use Pre-Built Binary**
+```bash
+# Download pre-built binary from:
+# https://github.com/ggerganov/llama.cpp/releases
+
+./llama-cli \
+  --hf-repo "turquise/MedQA_q4" \
+  --hf-file MedQA.Q4_K_M.gguf \
+  -p "What is Medullary Sponge Kidney?"
+```
+#### **Build from Source Code**
+```bash
+git clone https://github.com/ggerganov/llama.cpp.git
+cd llama.cpp
+cmake -B build -DLLAMA_CURL=ON
+cmake --build build -j --target llama-cli
+
+./build/bin/llama-cli \
+  --hf-repo "turquise/MedQA_q4" \
+  --hf-file MedQA.Q4_K_M.gguf \
+  -p "What is Medullary Sponge Kidney?"
+```
+
+---
+
+## 🤖 Example Usages
+This model can assist with the following tasks:
+
+- Answering medical questions:
+```python
+question = "What are the symptoms of diabetes?"
+output = llm(question, max_tokens=512)
+print(output)
+```
+- Providing insights for healthcare education: Example: Answering queries about diseases, treatments, and chronic conditions.
+- Supporting virtual assistants by handling frequently asked healthcare-related questions.
+
+---
+
+## ⚠️ Disclaimer
+
+- This model **does not provide medical advice** and should not replace professional medical consultation.
+- For any health-related questions or concerns, please consult a doctor or a licensed healthcare professional.
+
+---
+
+## 🤖 Applications
+
+This fine-tuned model can be used to:
+- Build **virtual assistants** and chatbots for healthcare-related queries.
+- Assist healthcare professionals by handling routine inquiries.
+- Enhance **medical education platforms** with AI-powered insights.
+
+---
+
+## 📜 Acknowledgements
+
+- Dataset: [Huggingface Hub - MedQuad](https://huggingface.co/datasets/keivalya/MedQuad-MedicalQnADataset).
+- Fine-tuning framework: [Unsloth](https://github.com/unslothai/unsloth).
+
+If you use this project or dataset in your research, please credit the original authors.
+
+---
+
+## 📝 License
+
+This project is open-sourced under the **CC0 1.0 Universal License**. See the dataset [license details](https://creativecommons.org/publicdomain/zero/1.0/).
+
+---
+
+## 📧 Contact
+
+For questions or collaboration, reach out via [HF Model Community](https://huggingface.co/turquise/MedQA_q4/discussions).