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Browse files- pages/1_Sentiment_Analysis.py +0 -54
- pages/2_Zero-shot_Classification.py +0 -4
- pages/3_Text_Generation.py +0 -4
- pages/4_Mask_filling.py +0 -4
- pages/5_Named_Entity_Recognition.py +0 -4
- pages/6_Question_Answering.py +0 -4
- pages/7_Summarization.py +0 -4
- pages/8_ Translation.py +0 -4
pages/1_Sentiment_Analysis.py
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import streamlit as st
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import time
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from transformers import pipeline
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st.title('Sentiment Analysis')
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st.subheader("Example: Single statement analysis")
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with st.spinner('Wait for it...'):
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time.sleep(5)
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classifier = pipeline("sentiment-analysis")
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results = classifier("Transformers library is very helpful.")
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code = '''
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from transformers import pipeline
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classifier = pipeline("sentiment-analysis")
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results = classifier("Transformers library is very helpful.")
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'''
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st.code(code, language='python')
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st.write("Output:")
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st.success(results)
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st.divider()
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st.subheader("Example: Multiple statements analysis")
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with st.spinner('Wait for it...'):
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time.sleep(5)
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code = '''
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from transformers import pipeline
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classifier = pipeline("sentiment-analysis")
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results = classifier([
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"This is quick tutorial site.",
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"I learnt new topics today.",
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"I do not like lengthy tutorials."
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])
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'''
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st.code(code, language='python')
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results = classifier([
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"This is quick tutorial site.",
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"I learnt new topics today.",
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"I do not like lengthy tutorials."
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])
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st.write("Output:")
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st.success(results)
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pages/2_Zero-shot_Classification.py
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import streamlit as st
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st.title('Zero-shot classification')
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pages/3_Text_Generation.py
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import streamlit as st
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st.title('Text Generation')
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pages/4_Mask_filling.py
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import streamlit as st
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st.title('Mask Filling')
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pages/5_Named_Entity_Recognition.py
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import streamlit as st
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st.title('Named Entity Recognition')
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pages/6_Question_Answering.py
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import streamlit as st
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st.title('Question Answering')
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pages/7_Summarization.py
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import streamlit as st
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st.title('Summarization')
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pages/8_ Translation.py
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import streamlit as st
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st.title('Translation')
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