| # 🩺 TinyLlama Medical Assistant | |
| A fine-tuned TinyLlama 1.1B model specialized in allopathic medicine, trained using LoRA (Low-Rank Adaptation) on a custom medical dataset. | |
| ## 🎯 Features | |
| - **Fine-tuned Model**: Specialized knowledge of 10+ common medicines | |
| - **LoRA Adaptation**: Efficient fine-tuning with only 2.2M trainable parameters | |
| - **4-bit Quantization**: Memory-efficient inference | |
| - **User Authentication**: Role-based access (admin, doctor, student) | |
| - **Medical Disclaimer**: Safety warnings on all responses | |
| - **Interactive UI**: Clean Streamlit interface with adjustable parameters | |
| ## 📊 Model Details | |
| - **Base Model**: TinyLlama-1.1B-Chat-v1.0 | |
| - **Fine-tuning Method**: LoRA (r=8, alpha=16) | |
| - **Training Data**: 500 medical Q&A pairs | |
| - **Training Accuracy**: 97.83% | |
| - **Medicines Covered**: Paracetamol, Ibuprofen, Amoxicillin, Metformin, Atorvastatin, Amlodipine, Omeprazole, Cetirizine, Azithromycin, Losartan | |
| ## 🚀 Quick Start | |
| ### Local Installation | |
| ```bash | |
| # Clone the repository | |
| git clone https://github.com/yourusername/medical-assistant.git | |
| cd medical-assistant | |
| # Install dependencies | |
| pip install -r requirements.txt | |
| # Run the app | |
| streamlit run app.py | |
| ``` | |
| ### Login Credentials | |
| ``` | |
| Username: admin Password: admin123 | |
| Username: doctor Password: doc123 | |
| Username: student Password: student123 | |
| ``` | |
| ## 📁 Project Structure | |
| ``` | |
| medical-assistant/ | |
| ├── app.py # Main Streamlit application | |
| ├── requirements.txt # Python dependencies | |
| ├── .streamlit/ | |
| │ └── config.toml # Streamlit configuration | |
| ├── tinyllama-medical-lora/ # Fine-tuned model weights | |
| │ ├── adapter_config.json | |
| │ ├── adapter_model.safetensors | |
| │ └── tokenizer files... | |
| └── README.md | |
| ``` | |
| ## 💡 Example Queries | |
| - "What is Paracetamol used for?" | |
| - "Tell me about Ibuprofen" | |
| - "What is Metformin?" | |
| - "Uses of Amoxicillin" | |
| - "What is Atorvastatin for?" | |
| ## ⚙️ Model Parameters | |
| Adjust these in the sidebar: | |
| - **Temperature** (0.1-1.5): Controls randomness | |
| - **Max Tokens** (32-256): Response length | |
| - **Top-p** (0.1-1.0): Nucleus sampling | |
| ## ⚠️ Medical Disclaimer | |
| This AI assistant is for educational purposes only. Always consult a qualified healthcare provider for medical advice. | |
| ## 🔧 Technical Stack | |
| - **Framework**: Streamlit | |
| - **Model**: TinyLlama 1.1B + LoRA | |
| - **Libraries**: Transformers, PEFT, BitsAndBytes, PyTorch | |
| - **Quantization**: 4-bit NF4 | |
| ## 📄 License | |
| MIT License | |
| ## 👥 Authors | |
| Your Name - Medical AI Research | |
| ## 🙏 Acknowledgments | |
| - TinyLlama team for the base model | |
| - Hugging Face for transformers library | |
| - PEFT library for LoRA implementation | |