| # Steps to Run the Model | |
| 1. **Clone the Repository**: | |
| Open your command line interface (CLI) and clone the repository using: | |
| ```bash | |
| git clone https://huggingface.co/webslate/transactify | |
| ``` | |
| 2. **Create the Virtual Environment**: | |
| Navigate to the project directory and create a virtual environment: | |
| ```bash | |
| python -m venv transactify_venv | |
| ``` | |
| 3. **Activate the Virtual Environment**: | |
| To activate the virtual environment, follow these steps: | |
| - Open your command line interface (CLI). | |
| - Type the following commands: | |
| ```bash | |
| cd transactify_venv | |
| cd Scripts | |
| activate | |
| ``` | |
| 4. **Install Required Libraries**: | |
| After activating the virtual environment, install the necessary libraries by typing: | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| 5. **Run the Data Preprocessing Code**: | |
| Execute the data preprocessing script by typing: | |
| ```bash | |
| python data_preprocessing.py | |
| ``` | |
| 6. **Run the LSTM Model Code**: | |
| Train the LSTM model by executing: | |
| ```bash | |
| python LSTM_model.py | |
| ``` | |
| 7. **Generate the H5 File**: | |
| After training, you can generate the model file (`transactify.h5`). | |
| 8. **Run the Prediction Code**: | |
| To make predictions using the trained model, type: | |
| ```bash | |
| python main.py | |
| ``` | |
| Following these steps will set up and run the Transactify model for predicting transaction categories based on descriptions. | |