Update app.py

app.py

@@ -10,7 +10,7 @@ zero = torch.Tensor([0]).cuda()
 print(zero.device)
 
 device = 0 if torch.cuda.is_available() else -1
-torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+
 # Load LLM model for classification
 classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli",device=device)
 
@@ -34,7 +34,7 @@ sub_request_types = {
 }
 
 # Function to extract text from PDFs
-@spaces.GPU
+
 def extract_text_from_pdf(pdf_path):
     with pdfplumber.open(pdf_path) as pdf:
         text = "\n".join(page.extract_text() for page in pdf.pages if page.extract_text())
@@ -56,7 +56,7 @@ def classify_text(text):
     return f"Request Type: {main_category}\nSub Request Type: {sub_category}\nConfidence Score: {confidence:.2f}"
 
 # Gradio UI
-@spaces.GPU
+
 def process_pdf(file):
     text = extract_text_from_pdf(file.name)
     return classify_text(text)