Update models/hsd_tr.py

models/hsd_tr.py

@@ -5,22 +5,21 @@ import time
 from transformers import pipeline
 import os
 
-sentiment_pipeline = pipeline(task = "text-classification", model = "gritli/bert-sentiment-analyses-imdb")
-label_dict = {'LABEL_0': 'Hate', 'LABEL_1': 'Non-hate'}
+# 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]
 
-#st.title("Hate Speech Detection in Turkish with HuggingFace Spaces")
-#st.write("Enter a Turkish sentence here:")
-#user_input = st.text_input(" ")
-
-user_input = st.text_input("Enter your text here:",)
+        strength_tr = " "
+        st.write(f"Detection: {sentiment_tr},  Strength: {strength_tr}")
+        
 
-#if user_input:
-if st.button("Click for predictions!"):
-    with st.spinner('Generating predictions...'):
-        result = sentiment_pipeline(user_input)
-        sentiment = result[0]["label"]
-        label_dict = {'LABEL_0': 'Hate', 'LABEL_1': 'Non-hate'}
-        sentiment = label_dict[sentiment]
-        #st.write(f"Detection: {sentiment}")
-        #st.success(sentiment)