Update app.py

app.py

@@ -22,9 +22,7 @@ class BertForSTS(torch.nn.Module):
         #self.bert = AutoModelForSequenceClassification.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth")
         self.bert = models.Transformer(param_model_name, max_seq_length=param_max_length)
 
-        if(param_freeze):
-          for p in self.bert.parameters():
-            p.requires_grad = False
+
         dimension= self.bert.get_word_embedding_dimension()
         #print(dimension)
         self.pooling_layer = models.Pooling(dimension)
@@ -53,7 +51,7 @@ class BertForSTS(torch.nn.Module):
         return x
 model_load_path = "IBounhas/riadh/bert-sts-15.pt"
 model = BertForSTS()
-model.load_state_dict(torch.load(model_save_path, map_location=torch.device('cpu')))
+model.load_state_dict(torch.load(model_load_path, map_location=torch.device('cpu')))
 model.to(device)
 
 def predict_similarity(sentence_pair):