models/hsdtr.py

#import streamlit as st
#from transformers import pipeline

# Turkish 
#sentiment_pipeline_tr = pipeline(task = "text-classification", model = "SoDehghan/BERTurk-hate-speech")  # "gritli/bert-sentiment-analyses-imdb"
#header_tr = r"$\textsf{\scriptsize HSD in Turkish}$"
#st.subheader(header_tr)

#tr_input = st.text_area("Enter your text here:", height=50, key="tr_input")  #height=30
#if st.button("Click for predictions!", key="tr_predict"):
    #st.write(" ")
    #with st.spinner('Generating predictions...'):
        #result_tr = sentiment_pipeline_tr(tr_input)
        #sentiment_tr = result_tr[0]["label"]
        #label_dict = {'LABEL_1': 'Hate ❌  ', 'LABEL_0': 'Non-hate ✅  '}  #🚫
        #sentiment_tr = label_dict[sentiment_tr]

        #strength_tr = " "
        #st.write(f"Detection: {sentiment_tr},  Strength: {strength_tr}")