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| import streamlit as st | |
| from transformers import pipeline | |
| # widget for selecting langugae model | |
| # available sentiment analysis models: https://huggingface.co/models?pipeline_tag=text-classification&sort=downloads&search=sentiment | |
| # we take the first 5 most downloaded ones. | |
| language_model = st.selectbox( | |
| "Select the Pretrained Language Model you'd like to use", | |
| ( | |
| "finiteautomata/bertweet-base-sentiment-analysis", | |
| "siebert/sentiment-roberta-large-english", | |
| "cardiffnlp/twitter-roberta-base-sentiment", | |
| "Seethal/sentiment_analysis_generic_dataset", | |
| "nlptown/bert-base-multilingual-uncased-sentiment", | |
| ), | |
| ) | |
| # pass the model to transformers pipeline - model selection component. | |
| sentiment_analysis = pipeline(model=language_model) | |
| # get text entry from users | |
| data = st.text_input( | |
| "Enter Text", "Just started school at NYU! Looking forward to this new chapter!" | |
| ) | |
| if st.button("Submit"): | |
| results = sentiment_analysis([data]) | |
| st.write(results) | |