Update app.py

app.py

@@ -28,7 +28,7 @@ torch_dtype = torch.float32
 
 pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-large", device=device, torch_dtype=torch_dtype)
 
-# @spaces.GPU(queue=True)
+@spaces.GPU(queue=True)
 
 # Initialize processor and pipeline
 processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-large")
@@ -113,7 +113,7 @@ summarization_model = AutoModelForSeq2SeqLM.from_pretrained("t5-base", return_di
 summarization_tokenizer = AutoTokenizer.from_pretrained("t5-base")
 summarization_model.to(device)
 
-# @spaces.GPU(queue=True)
+@spaces.GPU(queue=True)
 def summarize_text(text):
     preprocessed_text = preprocess_text(text)
     if preprocessed_text is None:
@@ -200,7 +200,7 @@ from PIL import Image
 
 def save_to_pdf(text, summary):
     pdf = FPDF()
-    pdf.add_page()alt="Banner Image"
+    pdf.add_page()
     pdf.set_font("Arial", size=12)
 
     if text: