Update app.py

app.py

@@ -13,7 +13,7 @@ led_tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-reranker-v2-m3")
 summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", tokenizer="sshleifer/distilbart-cnn-12-6", framework="pt")
 
 # Load the model separately
-model = AutoModelForSeq2SeqLM.from_pretrained("BAAI/bge-reranker-v2-m3")
+model = AutoModelForSequenceClassification.from_pretrained("BAAI/bge-reranker-v2-m3")
 
 # Move the model to CUDA if available
 if torch.cuda.is_available():