|
|
| # 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. |
|
|