File size: 2,673 Bytes
9f65e0d 0aaefc8 9f65e0d 6ed966a 9f65e0d bd26754 9f65e0d 72640a4 9f65e0d defb642 72640a4 aa02adf 72640a4 defb642 9f65e0d defb642 9f65e0d defb642 780e5cb defb642 7a34d4d 9f65e0d fda4b3f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
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='centered')
#welcome Animation
com.iframe("https://embed.lottiefiles.com/animation/149093")
st.markdown("<h1 style='text-align: center'> Tweet Sentiments </h1>",unsafe_allow_html=True)
#Create a form to take user inputs
with st.form(key='tweet',clear_on_submit=False):
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')
submit=st.form_submit_button('submit')
if submit:
#Check text
if text=="":
st.error('Empty text')
else:
st.success('Text received',icon='✅')
#Select a model
exp=st.expander(label='Choose a model and Click Continue or go ahead and Click continue to use default')
models={'Roberta': 'Junr-syl/sentiments_analysis_Roberta',
'Bert': 'Junr-syl/sentiments_analysis_upgrade',
'Distilbert':'Junr-syl/sentiments_analysis_DISTILBERT'}
with exp:
model=st.selectbox('Which model would you want to Use?',('Bert','Roberta','Distilbert'))
selected_model=models[model]
#Click continue if no model is selected
Cont=st.button('Continue','Continue processing input')
#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 Cont:
#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':
with col1:
com.iframe("https://embed.lottiefiles.com/animation/125694")
col2.write('NEGATIVE')
col3.write(f'{score*100:.2f}%')
elif lable=='POSITIVE':
with col1:
com.iframe("https://embed.lottiefiles.com/animation/148485")
col2.write('POSITIVE')
col3.write(f'{score*100:.2f}%')
else:
with col1:
com.iframe("https://embed.lottiefiles.com/animation/136052")
col2.write('NEUTRAL')
col3.write(f'{score*100:.2f}%')
|