import streamlit as st from transformers import pipeline from ModelDriver import * import numpy as np # Add a title st.title('GPT Detection Demo') # Add 4 options for 4 models ModelOption = st.sidebar.selectbox( 'Which Model do you want to use?', ('RobertaSentinel', 'RobertaClassifier'), ) DatasetOption = st.sidebar.selectbox( 'Which Dataset do you want to use?', ('OpenGPT', 'CSAbstract'), ) text = st.text_area('Enter text here', '') if st.button('Generate'): if ModelOption == 'RobertaSentinel': if DatasetOption == 'OpenGPT': result = RobertaSentinelOpenGPTInference(text) elif DatasetOption == 'CSAbstract': result = RobertaSentinelCSAbstractInference(text) elif ModelOption == 'RobertaClassifier': if DatasetOption == 'OpenGPT': result = RobertaClassifierOpenGPTInference(text) elif DatasetOption == 'CSAbstract': result = RobertaClassifierCSAbstractInference(text) Prediction = "Human Written" if not np.argmax(result) else "Machine Generated" print(f"Prediction: {Prediction} ") print(f"Probabilty:", max(result)) st.write(result)