Delete app (1).py

app (1).py

@@ -1,73 +0,0 @@
-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%}')