# VishwamAI

VishwamAI is an advanced language model based on the Transformer architecture, designed for various natural language processing tasks.

## Installation

1. Clone the repository:
   ```
   git clone https://github.com/VishwamAI/chat-agent.git
   cd chat-agent
   ```

2. Install the required packages:
   ```
   pip install -r requirements.txt
   ```

## Usage

### Training the model

To train the VishwamAI model, run:

```
python scripts/train.py
```

This script will load the configuration from `configs/default_config.yaml`, initialize the model and datasets, and start the training process.

### Generating text

To generate text using a trained model, use:

```
python scripts/generate_text.py --prompt "Your prompt here" --max_length 100
```

### Evaluating the model

To evaluate the model on a test dataset, run:

```
python scripts/evaluate.py --test_file path/to/test/file.txt
```

## Configuration

You can modify the model and training configuration by editing the `configs/default_config.yaml` file.

## Documentation

For more detailed information about the model architecture, training process, and API reference, please refer to the `docs/` directory.

## Contributing

Contributions to VishwamAI are welcome! Please refer to the `CONTRIBUTING.md` file for guidelines on how to contribute to this project.

## License

This project is licensed under the MIT License. See the `LICENSE` file for details.

This structure and these files provide a solid foundation for your improved VishwamAI model. The code is more modular and organized, making it easier to maintain and extend. The `README.md` file gives users an overview of how to use your model.

To use this improved version:

1. Set up the folder structure as shown above.
2. Copy the provided code into their respective files.
3. Implement any missing functions (e.g., evaluation logic, text generation).
4. Add necessary dependencies to `requirements.txt`.
5. Create appropriate documentation in the `docs/` directory.