File size: 656 Bytes
a63248d 209d195 a63248d 209d195 a63248d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 |
import streamlit as st
from transformers import pipeline
sentiment_pipeline = pipeline("sentiment-analysis")
st.title("Sentiment Analysis")
st.write("Welcome sentiment analysis Spaces' built using Streamlit and Hugging Face's Transformers library. The application allows users to input a sentence and receive a real-time sentiment analysis result, along with a confidence score.")
user_input = st.text_input("Write a sentence please:")
if user_input:
result = sentiment_pipeline(user_input)
sentiment = result[0]["label"]
confidence = result[0]["score"]
st.write(f"Sentiment: {sentiment}")
st.write(f"Confidence: {confidence:.2f}")
|