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import streamlit as st
import time
from transformers import pipeline
st.title('Sentiment Analysis')
st.subheader("Example: Single statement analysis")
with st.spinner('Wait for it...'):
time.sleep(5)
classifier = pipeline("sentiment-analysis")
results = classifier("Transformers library is very helpful.")
code = '''
from transformers import pipeline
classifier = pipeline("sentiment-analysis")
results = classifier("Transformers library is very helpful.")
'''
st.code(code, language='python')
st.write("Output:")
st.success(results)
st.divider()
st.subheader("Example: Multiple statements analysis")
with st.spinner('Wait for it...'):
time.sleep(5)
code = '''
from transformers import pipeline
classifier = pipeline("sentiment-analysis")
results = classifier([
"This is quick tutorial site.",
"I learnt new topics today.",
"I do not like lengthy tutorials."
])
'''
st.code(code, language='python')
results = classifier([
"This is quick tutorial site.",
"I learnt new topics today.",
"I do not like lengthy tutorials."
])
st.write("Output:")
st.success(results)
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