app modified

app.py

@@ -303,8 +303,7 @@ class ModeloDataset:
             MAX_LEN=128
             ids=pad_sequences(ids,maxlen=MAX_LEN,dtype="long",truncating="post", padding="post")
             input_ids = torch.tensor(ids) 
-            #model = RobertaForTokenClassification.from_pretrained("BSC-LT/roberta_model_for_anonimization")   
-                   
+                             
             self.model = RobertaForTokenClassification.from_pretrained("BSC-LT/roberta_model_for_anonimization")
             with torch.no_grad():
              logits = self.model(input_ids).logits
@@ -361,7 +360,7 @@ class ModeloDataset:
             print('ig_tok',ig_tok) 
             
             for items in _predicted_tokens_classes:
-                if i<len(tokenized_text[i]):
+                if i<len(new_tokens[i]):
                     print('len(_predicted_tokens_classes)',len(items))
                     aux=self.reordenacion_identificadores(ig_tok[i],items)
                     new_identificadores.append(aux)