Create hsd_ar.py

hsd_ar.py

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+import awesome_streamlit as ast
+import streamlit as st
+import requests
+import time 
+from transformers import pipeline
+import os
+
+import streamlit as st
+from transformers import pipeline
+
+sentiment_pipeline = pipeline(task = "text-classification", model = "gritli/bert-sentiment-analyses-imdb")
+
+st.title("Hate Speech Detection with HuggingFace Spaces")
+st.write("Enter a sentence to detect its hateful:")
+
+label_dict = {'LABEL_0': 'Hate', 'LABEL_1': 'Non-hate'}
+
+user_input = st.text_input("")
+if user_input:
+    result = sentiment_pipeline(user_input)
+    sentiment = result[0]["label"]
+
+    sentiment = label_dict[sentiment]
+    st.write(f"Sentiment: {sentiment}")