app.py

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)