app.py

import streamlit as st
import torch
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification, pipeline


st.title("Toxic Tweets Analyzer")
image = "kanye_tweet.jpg"
st.image(image, use_column_width=True)


#select model
model_name = st.selectbox("Select model", ["distilbert-base-uncased-finetuned-sst-2-english", "finiteautomata/bertweet-base-sentiment-analysis"])
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = TFAutoModelForSequenceClassification.from_pretrained(model_name)
clf = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer, framework="pt")

#form
with st.form("my_form"):
    submitted = st.form_submit_button("Analyze")
    tweet = st.text_area("enter tweet here:", value="i'm nice at ping pong")
    if submitted:
        out = clf(tweet)
            
        #loading bar
        st.spinner(text="...")
        st.success('Done!')
        st.balloons()
        st.json(out)