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