|
--- |
|
license: apache-2.0 |
|
datasets: |
|
- stanfordnlp/imdb |
|
- uoft-cs/cifar10 |
|
- superlazycoder/slc-titanic |
|
language: |
|
- en |
|
metrics: |
|
- bertscore |
|
library_name: transformers |
|
pipeline_tag: text-generation |
|
tags: |
|
- code |
|
- medical |
|
--- |
|
# Agentic Unified Mind UANN |
|
|
|
This repository contains the implementation of the Agentic Unified Mind Universal Adaptive Neural Network (UANN), a multi-modal AI model designed to integrate text, image, and structured data processing. The model uses advanced neural network architectures and reinforcement learning to deliver robust performance across various applications. |
|
|
|
## Model Description |
|
|
|
The Agentic Unified Mind UANN integrates: |
|
- Text processing using BERT. |
|
- Image processing using ResNet50. |
|
- Structured data processing with dense neural networks. |
|
- Reinforcement learning for autonomous decision-making. |
|
|
|
## Features |
|
|
|
- **Multi-modal Inputs:** Handles text, images, and structured data. |
|
- **Advanced Neural Network Architectures:** Uses BERT for text, ResNet50 for images, and dense layers for structured data. |
|
- **Unified Cognitive Framework:** Combines information from multiple modalities for better decision-making. |
|
- **Reinforcement Learning:** Enhances the model's ability to learn and adapt from interactions. |
|
|
|
## Setup |
|
|
|
### 1. Installation |
|
|
|
Install the required dependencies: |
|
|
|
```bash |
|
pip install -r requirements.txt |
|
``` |
|
|
|
### 2. Model Training |
|
|
|
To train the model, run: |
|
|
|
```bash |
|
python app.py |
|
``` |
|
|
|
### 3. API Integration |
|
|
|
The project includes a Flask API for storing and retrieving model predictions. |
|
|
|
**API Setup:** |
|
|
|
1. Install Flask and necessary libraries: |
|
|
|
```bash |
|
pip install flask flask_sqlalchemy flask_cors |
|
``` |
|
|
|
2. Configure your database URI in `api.py`. |
|
|
|
3. Run the Flask API: |
|
|
|
```bash |
|
python api.py |
|
``` |
|
|
|
### 4. Gradio Interface |
|
|
|
To launch the Gradio interface: |
|
|
|
```bash |
|
python app.py |
|
``` |
|
|
|
### Directory Structure |
|
|
|
``` |
|
agentic_uann_model/ |
|
├── app.py |
|
├── api.py |
|
├── requirements.txt |
|
└── models/ |
|
└── model_files/ |
|
``` |
|
|
|
## Deployment |
|
|
|
1. Push your repository to Hugging Face Spaces. |
|
2. Navigate to Hugging Face Spaces and create a new Space. |
|
3. Select "Gradio" as the framework. |
|
4. Connect your GitHub repository or upload the files directly. |
|
5. Choose the desired hardware, such as an A100 40GB GPU. |
|
|
|
## Usage |
|
|
|
- **Chat Interface:** Interact with the model using a chat interface. |
|
- **Code Execution:** Execute code snippets and view outputs. |
|
|
|
## License |
|
|
|
This project is licensed under the Apache 2.0 License. See the [LICENSE](LICENSE) file for more details. |
|
|
|
--- |
|
|
|
By following this guide, you will be able to set up and deploy the Agentic Unified Mind UANN, leveraging its multi-modal processing capabilities and reinforcement learning framework. |
