| import streamlit as st | |
| from transformers import pipeline | |
| st.title('Sentiment Analysis using Transformers pipeline function') | |
| # steamlit form | |
| form = st.form(key='sentiment-form') | |
| user_input = form.text_area(label = 'Enter your text', value = "I love steamlit and hugging face!") | |
| submit = form.form_submit_button('Submit') | |
| if submit: | |
| classifier = pipeline("sentiment-analysis") #using the pipeline() function | |
| result = classifier(user_input)[0] | |
| label = result['label'] | |
| score = result['score'] | |
| if label == 'POSITIVE': | |
| st.success(f'{label} sentiment (score: {score})') | |
| else: | |
| st.error(f'{label} sentiment (score: {score})') | |
| st.write('References:') | |
| st.write('1. https://medium.com/@rtkilian/deploy-and-share-your-sentiment-analysis-app-using-streamlit-sharing-2ba3ca6a3ead') | |
| st.write('2. https://huggingface.co/learn/nlp-course/chapter1/3?fw=pt') | |
| st.write('3. https://docs.streamlit.io/library/api-reference/widgets/st.text_input') | |