Update app.py

app.py

@@ -18,7 +18,7 @@ def predict(title, summary, tokenizer, model):
     text = title + "\n" + summary
     tokens = tokenizer.encode(text)
     with torch.no_grad():
-        logits = model(torch.as_tensor([tokens], device=device))[0]
+        logits = model(torch.as_tensor([tokens]))[0]
         probs = torch.softmax(logits[-1, :], dim=-1).data.cpu().numpy()
     
     classes = np.flip(np.argsort(probs))