| import streamlit as st | |
| from transformers import pipeline | |
| st.cache_resource(ttl=300) | |
| pipe = pipeline(task="text-classification",model="yartyjung/Fake-Review-Detector") | |
| st.title(":green[Real ] :rainbow[or] :red[Fake]") | |
| st.divider() | |
| text = st.text_input("Your :red[suspicious] review here :sunglasses:",value="") | |
| if st.button("predict"): | |
| if text is not None: | |
| predictions = pipe(text) | |
| if predictions[0]['label'] == 'fake': | |
| for p in predictions: | |
| st.subheader(f":red[FAKE] :blue[{ round(p['score'] * 100, 1)} %]") | |
| elif predictions[0]['label'] == 'real': | |
| for p in predictions: | |
| st.subheader(f":green[REAL] :blue[{ round(p['score'] * 100, 1)} %]") | |
| st.divider() | |
| st.markdown(":red[***disclaimer*** This is a prediction by an _AI_, which might turn out incorrect.]") | |
| url = "https://huggingface.co/yartyjung/Fake-Review-Detector" | |
| st.markdown(":yellow[check out model at this [link](%s)]" % url) |