updating to use new model for summary

app.py

@@ -20,7 +20,8 @@ model = ASRModel.from_pretrained(model_name=MODEL_NAME)
 model.eval()
 
 # Load the summarization model once at startup
-summarizer = pipeline("summarization", model="Falconsai/text_summarization", device="cpu")
+#summarizer = pipeline("summarization", model="Falconsai/text_summarization", device="cpu")
+ summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
 
 def get_audio_segment(audio_path, start_second, end_second):
     """
@@ -248,7 +249,7 @@ def summarize_transcript(transcript):
     try:
         gr.Info("Generating summary...", duration=2)
         # The pipeline returns a list of dictionaries
-        result = summarizer(transcript, max_length=250, min_length=50, do_sample=False)
+        result = summarizer(transcript, max_length=250, min_length=50, num_beams=4, early_stopping=True)
         # Extract the summary text from the first result
         summary = result[0]['summary_text']
         return summary