Update app.py

app.py

@@ -6,16 +6,15 @@ def Model():
   from transformers import DebertaTokenizer, DebertaForSequenceClassification
   tokenizer = DebertaTokenizer.from_pretrained("microsoft/deberta-base")
   model = DebertaForSequenceClassification.from_pretrained("microsoft/deberta-base", num_labels=8)
-  bn_state_dict = torch.load('model_weights.pt')
+  bn_state_dict = torch.load('model_weights.pt', map_location=torch.device('cpu'))
   model.load_state_dict(bn_state_dict)
   return model, tokenizer
 
 def Predict(model, tokenizer, text):
   res = tokenizer(s, padding=True, truncation=True, return_tensors="pt", max_length=512)
-  res.to("cuda:0")
   res = model(**res)
   logits = res.logits.softmax(dim=1)
-  logits = logits.cpu().detach().numpy()[0]
+  logits = logits.numpy()[0]#.cpu().detach().numpy()[0]
   return logits
   
 def Print(logits, dictionary):