import streamlit as st import requests import time from transformers import pipeline import os # Set the page configuration st.set_page_config( page_title="Hate Speech Detection", page_icon="📖", #":bar_chart:" layout='centered' ) #title = r"$\textsf{\small Hate Speech Detection}$" #st.title(title) #st.write("In this HuggingFace space you will be able to use our Hate Speech Detection model built at [VERİM - Center of Excellence in Data Analytics - Sabanci University](https://github.com/verimsu).") # 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"): with st.spinner('Generating predictions...'): st.write(" ") 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}") st.write(" ") # Arabic sentiment_pipeline_ar = pipeline(task = "text-classification", model = "SoDehghan/BERTurk-hate-speech") header_ar = r"$\textsf{\scriptsize HSD in Arabic}$" st.subheader(header_ar) ar_input = st.text_area("Enter your text here:", height=50 , key="ar_input") if st.button("Click for predictions!", key="ar_predict"): with st.spinner('Generating predictions...'): st.write(" ") result_ar = sentiment_pipeline_ar(ar_input) sentiment_ar = result_ar[0]["label"] label_dict = {'LABEL_1': 'Hate ❌ ', 'LABEL_0': 'Non-hate ✅ '} sentiment_ar = label_dict[sentiment_ar] strength_tr = " " st.write(f"Detection: {sentiment_ar}, Strength: {strength_ar}") st.sidebar.title("Hate Speech Detection") #st.sidebar.write("In this HuggingFace space you can use Hate Speech Detection model built at [VERİM - Center of Excellence in Data Analytics - Sabanci University](https://github.com/verimsu).") st.sidebar.write('This tool is developed in the context of the EU project "Utilizing Digital Technology for Social Cohesion, Positive Messaging and Peace by Boosting Collaboration, Exchange and Solidarity" (EuropeAid/170389/DD/ACT/Multi) by [Sabanci University Center of Excellence in Data Analytics](https://github.com/verimsu).')