gguf endpoints_compatible region:us
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---


# **LLaMA-3.1 Medical Chatbot**

## **Model Description**
The **LLaMA-3.1 Medical Chatbot** is a  language model designed to assist users with medical-related questions. It is built upon the **LLaMA 3.1-8B** architecture, optimized for understanding and generating text relevant to the medical domain. The model leverages the **GGUF** format for efficient inference, making it compatible with lightweight frameworks like `llama.cpp`.

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## **Intended Use**
This model is intended to provide educational and general medical advice and excercised for a test. It is **not a substitute for professional medical consultation**.

### **Applications**
- Medical Q&A
- Educational insights about health and medicine
- Support for preliminary research in healthcare

---

## **Repository Structure**
The repository provides two main ways to interact with the model:

### **1. Streamlit App (`app.py`)**
This script provides a web-based interface for real-time interaction with the chatbot. Users can input their medical-related questions and receive responses directly in their browser.

#### **How to Run:**
1. Clone the repository.
2. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```
3. Run the app:
   ```bash
   streamlit run app.py
   ```
4. Open the Streamlit app in your browser (default: [http://localhost:8501](http://localhost:8501)).

---

### **2. Standalone Python Script (`run_model.py`)**
This script allows you to interact with the model via the command line. It’s a simple way to test the model directly without a web interface.

#### **How to Run:**
1. Clone the repository.
2. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```
3. Run the script:
   ```bash
   python run_model.py
   ```
4. Example Interaction:
   ```plaintext
   You: What is the treatment for high blood pressure?
   Model: Treatment options for high blood pressure include lifestyle changes, such as diet and exercise, and medications like ACE inhibitors or beta-blockers.
   ```

---

## **Model Details**

| **Property**         | **Details**             |
|-----------------------|-------------------------|
| **Architecture**      | LLaMA 3.1              |
| **Model Size**        | 8 Billion Parameters   |
| **Format**            | GGUF                   |
| **Quantization**      | Available              |
| **Tokenizer**         | LLaMA-BPE              |

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## **Limitations**
1. **Medical Advice Disclaimer**: This model is for informational purposes only and should not be used as a replacement for professional medical advice, diagnosis, or treatment.
2. **Bias and Accuracy**: The model may exhibit biases inherent in the training data and may provide inaccurate or incomplete information.

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## **Training Data**
The base LLaMA model was trained on a large dataset curated by Meta, optimized for general language understanding. This fine-tuned version incorporates additional medical data for domain-specific expertise.

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## **Performance**
The model demonstrates excellent capabilities in:
- Understanding medical terminology
- Answering medical queries with contextual relevance
- Generating coherent, informative responses

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## **System Requirements**
- **CPU/GPU**: Compatible with both, though GPU is recommended for faster inference.
- **Dependencies**:
  - `llama-cpp-python`
  - `streamlit`
  - `transformers`

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## **Acknowledgments**
- **Meta AI** for the LLaMA architecture.
- **Hugging Face** for hosting the model and enabling easy deployment.
- **llama.cpp** for efficient inference in Python and other environments.

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## **License**
This model is released under the same licensing terms as LLaMA 3.1. For details, refer to the [Meta AI license](https://github.com/facebookresearch/llama).

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## **Contact**
For issues or inquiries, feel free to reach out to:

**Maheen Bakhtyar**  
Email: [maheen.bakhtyar@gmail.com](mailto:maheen.bakhtyar@gmail.com) 