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501 Bytes
| import streamlit as st | |
| from transformers import pipeline | |
| classifier = pipeline("table-question-answering", model="deepset/gelectra-base-germanquad") | |
| def main(): | |
| st.title("Yelp review") | |
| with st.form("text_field"): | |
| text = st.text_area('enter some text:') | |
| # clicked==True only when the button is clicked | |
| clicked = st.form_submit_button("Submit") | |
| if clicked: | |
| results = classifier([text]) | |
| st.json(results) | |
| if __name__ == "__main__": | |
| main() |