app.py

import streamlit as st

st.markdown('### Ну привет!')

st.markdown("<img width=400px src='https://sun9-29.userapi.com/impg/XsnLY87wXQfninjPBb9NMaKpmRJfBcvSugQwXw/67T6-XmLNRc.jpg?size=900x600&quality=96&sign=7f8fd7d50dfd16ab81dba4db2a9d313b&c_uniq_tag=Tow2HrDf6VsRmeScG7n6RVm65qghWaWRfdrhDlTE28o&type=album'>", unsafe_allow_html=True)

from transformers import pipeline

classifier = pipeline("text-classification", "SkolkovoInstitute/russian_toxicity_classifier")

text = st.text_area("Напиши тут что-то, а я проверю насколько ты токсик")

st.markdown(f'{classifier(text)}')