Spaces:
Sleeping
Sleeping
File size: 2,603 Bytes
30c7664 ffc2586 30c7664 8e85438 30c7664 0b70d48 29e454e 30c7664 8e85438 30c7664 8e85438 30c7664 e41b98a 4f7fb4d 29e454e 30c7664 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
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"):
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}")
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...'):
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_ar = " "
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).') |