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app (1).py

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+import streamlit as st
+import streamlit.components.v1 as com
+#import libraries
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig
+import numpy as np
+#convert logits to probabilities
+from scipy.special import softmax
+from transformers import pipeline
+
+#Set the page configs
+st.set_page_config(page_title='Sentiments Analysis',page_icon='😎',layout='wide')
+
+#welcome Animation
+com.iframe("https://embed.lottiefiles.com/animation/149093")
+st.markdown("<h1 style='text-align: center'> Covid Vaccine Tweet Sentiments </h1>",unsafe_allow_html=True)
+st.write("<h2 style='font-size: 24px;'> These models were trained to detect how a user feels about the covid vaccines based on their tweets(text) </h2>",unsafe_allow_html=True)
+
+#Create a form to take user inputs
+with st.form(key='tweet',clear_on_submit=True):
+    #input text
+    text=st.text_area('Copy and paste a tweet or type one',placeholder='I find it quite amusing how people ignore the effects of not taking the vaccine')
+    #Set examples
+    alt_text=st.selectbox("Can't Type?  Select an Example below",('I hate the vaccines','Vaccines made from dead human tissues','Take the vaccines or regret the consequences','Covid is a Hoax','Making the vaccines is a huge step forward for humanity. Just take them'))
+    #Select a model
+    models={'Bert':'UholoDala/tweet_sentiments_analysis_bert',
+            'Distilbert':'UholoDala/tweet_sentiments_analysis_distilbert',
+            'Roberta':'UholoDala/tweet_sentiments_analysis_roberta'}
+    model=st.selectbox('Which model would you want to Use?',('Bert','Distilbert','Roberta'))
+     #Submit
+    submit=st.form_submit_button('Predict','Continue processing input')
+    
+selected_model=models[model]
+
+
+#create columns to show outputs
+col1,col2,col3=st.columns(3)
+col1.write('<h2 style="font-size: 24px;"> Sentiment Emoji </h2>',unsafe_allow_html=True)
+col2.write('<h2 style="font-size: 24px;"> How this user feels about the vaccine </h2>',unsafe_allow_html=True)
+col3.write('<h2 style="font-size: 24px;"> Confidence of this prediction </h2>',unsafe_allow_html=True)
+
+if submit:
+    #Check text
+    if text=="":
+        text=alt_text
+        st.success(f"input text is set to '{text}'")    
+    else:
+        st.success('Text received',icon='✅')
+        
+    #import the model
+    pipe=pipeline(model=selected_model)
+
+#pass text to model
+    output=pipe(text)
+    output_dict=output[0]
+    lable=output_dict['label']
+    score=output_dict['score']
+    
+        #output
+    if lable=='NEGATIVE' or lable=='LABEL_0':
+        with col1:
+            com.iframe("https://embed.lottiefiles.com/animation/125694")
+        col2.write('NEGATIVE')
+        col3.write(f'{score:.2%}')
+    elif lable=='POSITIVE'or lable=='LABEL_2':
+        with col1:
+            com.iframe("https://embed.lottiefiles.com/animation/148485")
+        col2.write('POSITIVE')
+        col3.write(f'{score:.2%}')
+    else:
+        with col1:
+            com.iframe("https://embed.lottiefiles.com/animation/136052")
+        col2.write('NEUTRAL')
+        col3.write(f'{score:.2%}')

requirements.txt

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+streamlit
+transformers
+transformers[torch]
+Scipy