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Create app.py
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app.py
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import streamlit as st
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import requests
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import time
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from transformers import pipeline
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import os
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# Set the page configuration
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st.set_page_config(
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page_title="Hate Speech Detection",
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page_icon="📖", #":bar_chart:"
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layout='centered'
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)
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#title = r"$\textsf{\small Hate Speech Detection}$"
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#st.title(title)
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#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).")
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# Turkish
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sentiment_pipeline_tr = pipeline(task = "text-classification", model = "SoDehghan/BERTurk-hate-speech") # "gritli/bert-sentiment-analyses-imdb"
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header_tr = r"$\textsf{\scriptsize HSD in Turkish}$"
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st.subheader(header_tr)
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tr_input = st.text_area("Enter your text here:", height=50, key="tr_input") #height=30
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if st.button("Click for predictions!", key="tr_predict"):
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with st.spinner('Generating predictions...'):
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result_tr = sentiment_pipeline_tr(tr_input)
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sentiment_tr = result_tr[0]["label"]
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label_dict = {'LABEL_1': 'Hate ❌', 'LABEL_0': 'Non-hate ✅'} #🚫
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sentiment_tr = label_dict[sentiment_tr]
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st.write(f"Detection: {sentiment_tr}")
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# Arabic
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sentiment_pipeline_ar = pipeline(task = "text-classification", model = "SoDehghan/BERTurk-hate-speech")
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header_ar = r"$\textsf{\scriptsize HSD in Arabic}$"
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st.subheader(header_ar)
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ar_input = st.text_area("Enter your text here:", height=50 , key="ar_input")
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if st.button("Click for predictions!", key="ar_predict"):
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with st.spinner('Generating predictions...'):
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result_ar = sentiment_pipeline_ar(ar_input)
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sentiment_ar = result_ar[0]["label"]
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label_dict = {'LABEL_1': 'Hate ❌', 'LABEL_0': 'Non-hate ✅'}
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sentiment_ar = label_dict[sentiment_ar]
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st.write(f"Detection: {sentiment_ar}")
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st.sidebar.title("Hate Speech Detection")
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#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).")
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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).')
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