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import json
import urllib
import streamlit as st
from transformers import pipeline
TEST_METRICS = 'https://huggingface.co/nbroad/longformer-base-health-fact/raw/main/test_results.json'
st.title('Veracity of a claim with pretrained longformer (PUBHEALTH)')
st.header('Claim')
claim = st.text_area(label='Enter a claim text in the box')
pl = pipeline('text-classification',
model='nbroad/longformer-base-health-fact')
st.header('Results')
st.write(pl(claim))
st.header('Self-reported test metrics')
with urllib.request.urlopen(TEST_METRICS) as response:
metrics = json.load(response)
st.write(metrics)
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