Update app.py

app.py

@@ -11,7 +11,8 @@ import textract
 @st.cache_resource(show_spinner=False)
 def load_summarization_pipeline():
     try:
-        summarizer = pipeline("summarization", model="recogna-nlp/ptt5-base-summ-xlsum")
+        # Initialize the summarization pipeline using the specified model.
+        summarizer = pipeline("summarization", model="deepseek-ai/deepseek-vl2-tiny")
         return summarizer
     except Exception as e:
         st.error(f"Error loading summarization model: {e}")
@@ -78,8 +79,8 @@ def summarize_text(text):
         return "No text available to summarize."
     
     try:
-        # Note: The summarization pipeline can have limitations on text length.
-        # If you face issues with long documents, consider summarizing in chunks.
+        # Note: The summarization pipeline might have limitations on text length.
+        # For long documents, consider splitting the text into smaller chunks.
         summary = summarizer(text, max_length=150, min_length=40, do_sample=False)
         return summary[0]["summary_text"]
     except Exception as e:
@@ -103,7 +104,7 @@ st.title("Resume Summarization App")
 st.markdown(
     """
     Upload your resume file — supported formats: **.doc**, **.docx**, and **.txt**.
-    The app will extract the text content from your resume and generate a summarization.
+    The app will extract the text content from your resume and generate a summary.
     """
 )