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import streamlit as st | |
from transformers import pipeline | |
# Create a title and a text input for the user to enter the text | |
st.title('Sentiment Analysis App') | |
text = st.text_input('Enter text here') | |
# Create a dropdown for the user to select the pre-trained model | |
model_name = st.selectbox( | |
'Select a pre-trained model', | |
['distilbert-base-uncased', 'distilbert-base-cased', 'bert-base-uncased', 'bert-base-cased', | |
'cardiffnlp/twitter-roberta-base-sentiment-latest', | |
'cardiffnlp/twitter-xlm-roberta-base-sentiment', | |
'j-hartmann/emotion-english-distilroberta-base', | |
'ProsusAI/finbert' | |
] | |
) | |
# Create a button to perform the sentiment analysis | |
if st.button('Analyze Sentiment'): | |
# Load the selected model | |
model = pipeline('sentiment-analysis', model=model_name) | |
# Perform sentiment analysis on the input text | |
result = model(text)[0] | |
# Print the sentiment label and score | |
st.write(f'Sentiment: {result["label"]}') | |
st.write(f'Score: {result["score"]}') | |