Update app.py

app.py

@@ -9,7 +9,7 @@ import torch
 model_names = ['python']
 
 models = {}
-model = AutoModel.from_pretrained(f'ZarahShibli/tmp_trainer',return_tensors="pt")
+model = AutoModel.from_pretrained(f'ZarahShibli/tmp_trainer',return_dict=False)
 
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 MAX_LEN = 200
@@ -45,7 +45,7 @@ def predict(comment_sentence):
     with torch.no_grad():
         outputs = model(ids, mask, token_type_ids)
     
-    fin_outputs.extend(torch.sigmoid(outputs).cpu().detach().numpy().tolist())
+    fin_outputs.extend(torch.sigmoid(torch.tensor(outputs.logits)).cpu().detach().numpy().tolist())
     print(fin_outputs)
     # Convert the outputs to boolean values based on the threshold
     outputs_boolean = np.array(fin_outputs) >= 0.25