Upload 6 files

app.py

@@ -1,54 +1,54 @@
-import streamlit as st
-from main import get_result
-
-def app():
-    if 'user_input' not in st.session_state:
-        st.session_state.user_input = ""
-
-    st.title("Tweet Classification")
-    
-    user_input = st.text_input(
-        "Enter a Tweet for Classification:", 
-        value=st.session_state.user_input, 
-        key="input_box"
-    )
-    st.session_state.user_input = user_input
-
-    st.subheader("Examples:")
-    
-    example1 = "i want to teach you love like you've never felt it before.  #quote #quotes #love #pakistan #allin216 #girls #boys #fashion   #feelings"
-    example2 = "Report: Google A.I. Is ‘Biased’ Against Gay People, Jews  http://www.breitbart.com/tech/2017/10/26/report-go..."
-    example3 = "I Hate #$%#$%Jewish%$#@%^^@#"
-    example4 = "i get to see my daddy today!! #80days #gettingfed"
-
-    col1, col2 = st.columns(2)
-    with col1:
-        if st.button(example1[:40] + "..."):
-            st.session_state.user_input = example1
-    with col2:
-        if st.button(example2[:40] + "..."):
-            st.session_state.user_input = example2
-
-    st.write("\n") 
-    
-    col1, col2 = st.columns(2)
-    with col1:
-        if st.button(example3[:40] + "..."):
-            st.session_state.user_input = example3
-    with col2:
-        if st.button(example4[:40] + "..."):
-            st.session_state.user_input = example4
-
-    st.write("\n") 
-    submit_button = st.button("Submit")
-    
-    if submit_button:
-        if user_input.strip():
-            result = get_result(user_input)
-            st.markdown(f'<p style="font-size: 20px; color: #FF6347; font-weight: bold;">Predicted Data: {result}</p>', unsafe_allow_html=True)
-        else:
-            st.warning("Please enter some text to classify.")
-    
-if __name__ == "__main__":
-    app()
-
+import streamlit as st
+from main import get_result
+
+def app():
+    if 'user_input' not in st.session_state:
+        st.session_state.user_input = ""
+
+    st.title("Tweet Classification")
+    
+    user_input = st.text_input(
+        "Enter a Tweet for Classification:", 
+        value=st.session_state.user_input, 
+        key="input_box"
+    )
+    st.session_state.user_input = user_input
+
+    st.subheader("Examples:")
+    
+    example1 = "You done a great job my friend!"
+    example2 = "I love machine learning"
+    example3 = "I Hate #$%#$%Jewish%$#@%^^@#"
+    example4 = "what the fuck is happening here"
+
+    col1, col2 = st.columns(2)
+    with col1:
+        if st.button(example1[:40] + "..."):
+            st.session_state.user_input = example1
+    with col2:
+        if st.button(example2[:40] + "..."):
+            st.session_state.user_input = example2
+
+    st.write("\n") 
+    
+    col1, col2 = st.columns(2)
+    with col1:
+        if st.button(example3[:40] + "..."):
+            st.session_state.user_input = example3
+    with col2:
+        if st.button(example4[:40] + "..."):
+            st.session_state.user_input = example4
+
+    st.write("\n") 
+    submit_button = st.button("Submit")
+    
+    if submit_button:
+        if user_input.strip():
+            result = get_result(user_input)
+            st.write(f"**Predicted Data:** {result}") 
+            st.markdown(f'<p style="font-size: 20px; color: #FF6347; font-weight: bold;">Predicted Data: {result}</p>', unsafe_allow_html=True)
+        else:
+            st.warning("Please enter some text to classify.")
+    
+if __name__ == "__main__":
+    app()

hate_speech_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:09fd4df266f53a52f9aec19d19f67fb962f1a1cd09972c2fbc5fbb2cea058926
-size 29807080
+oid sha256:b342d428aef894a8962d58be66c3c368964a340431db56ec48f433e94f0a118e
+size 29807064