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import streamlit as st | |
import transformers as t | |
import plotly.express as px | |
import pandas as pd | |
st.title("Phrase Feeling Analysis") | |
with st.spinner(text="Loading model..."): | |
classifier = t.pipeline("zero-shot-classification", | |
model="facebook/bart-large-mnli", | |
multi_class=True) | |
x = st.text_input("Enter your title here:") | |
candidate_labels = ['anger', 'sadness', 'fear', 'joy', 'interest', | |
'surprise', 'disgust', 'shame', 'guilt', 'compassion', 'other'] | |
if x != "": | |
with st.spinner(text="Evaluating your input..."): | |
output = classifier(x, candidate_labels) | |
# st.write(str(output)) | |
ordered_results = [] | |
for lbl in candidate_labels: | |
ind = output['labels'].index(lbl) | |
correct_order.append(output['scores'][ind]) | |
df = pd.DataFrame(dict(r=ordered_results, theta=candidate_labels)) | |
fig = px.line_polar(df, r='r', theta='theta', line_close=True) | |
fig.update_traces(fill='toself') | |
st.plotly_chart(fig) | |