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| import streamlit as st | |
| from transformers import pipeline | |
| from ModelDriver import * | |
| import numpy as np | |
| # Add a title | |
| st.title('GPT Detection Demo') | |
| st.write("This is a demo for GPT detection. You can use this demo to test the model. There are 3 variations of the Roberta Classifier Model, The model was trained on CHEAT, GPABenchmark, OpenGPT datasets.You can choose dataset variation of the model on the sidebar.") | |
| # st.write("Reference on how we built Roberta Sentinel: https://arxiv.org/abs/2305.07969") | |
| # # Add 4 options for 4 models | |
| # ModelOption = st.sidebar.selectbox( | |
| # 'Which Model do you want to use?', | |
| # ('RobertaClassifier'), | |
| # ) | |
| DatasetOption = st.sidebar.selectbox( | |
| 'Select Input Text Domain', | |
| ('General Text', 'Computer Science Abstract', 'Scientific Abstract'), | |
| ) | |
| text = st.text_area('Enter text here (max 512 words)', '', height=200) | |
| if st.button('Generate'): | |
| # if ModelOption == 'RobertaSentinel': | |
| # if DatasetOption == 'OpenGPT': | |
| # result = RobertaSentinelOpenGPTInference(text) | |
| # st.write("Model: RobertaSentinelOpenGPT") | |
| # elif DatasetOption == 'CSAbstract': | |
| # result = RobertaSentinelCSAbstractInference(text) | |
| # st.write("Model: RobertaSentinelCSAbstract") | |
| # if ModelOption == 'RobertaClassifier': | |
| # if DatasetOption == 'OpenGPT': | |
| # result = RobertaClassifierOpenGPTInference(text) | |
| # st.write("Model: RobertaClassifierOpenGPT") | |
| # elif DatasetOption == 'GPABenchmark': | |
| # result = RobertaClassifierGPABenchmarkInference(text) | |
| # st.write("Model: RobertaClassifierGPABenchmark") | |
| # elif DatasetOption == 'CHEAT': | |
| # result = RobertaClassifierCHEATInference(text) | |
| # st.write("Model: RobertaClassifierCHEAT") | |
| if DatasetOption == 'General Text': | |
| result = RobertaClassifierOpenGPTInference(text) | |
| st.write("Model: RobertaClassifierOpenGPT") | |
| elif DatasetOption == 'Computer Science Abstract': | |
| result = RobertaClassifierGPABenchmarkInference(text) | |
| st.write("Model: RobertaClassifierGPABenchmark") | |
| elif DatasetOption == 'Scientific Abstract': | |
| result = RobertaClassifierCHEATInference(text) | |
| st.write("Model: RobertaClassifierCHEAT") | |
| Prediction = "Human Written" if not np.argmax(result) else "Machine Generated" | |
| st.write(f"Prediction: {Prediction} ") | |
| st.write(f"Probabilty:", max(result)) | |