Update app.py

app.py

@@ -1,27 +1,28 @@
 import streamlit as st
 from transformers import pipeline
 
-
+# Your specific model repository
 MODEL_ID = "VoltIC/Automated-Text-Summarizer"
 
 @st.cache_resource
 def load_summarizer():
-    return pipeline("summarization", model=MODEL_ID, framework="pt")
+    return pipeline(
+        "summarization", 
+        model=MODEL_ID, 
+        subfolder="summarizer_model", 
+        framework="pt"
+    )
 
 summarizer = load_summarizer()
 
 st.title("📝 AI Text Summarizer")
-st.write("Enter a long article or legal document to get a concise summary.")
+st.write("Your model has loaded successfully from the subfolder!")
 
 input_text = st.text_area("Paste text here...", height=300)
 
 if st.button("Summarize"):
     if input_text.strip():
-        with st.spinner("Processing..."):
-            summary = summarizer(input_text, max_length=100, min_length=30, do_sample=False)
-            
-            st.success("Done!")
-            st.subheader("Summary:")
-            st.write(summary[0]['summary_text'])
-    else:
-        st.warning("Please paste some text first!")
+        with st.spinner("Summarizing..."):
+            summary = summarizer(input_text, max_length=100, min_length=30)
+            st.success("Summary Complete!")
+            st.write(summary[0]['summary_text'])