Update app.py

app.py

@@ -107,13 +107,16 @@ config = BertConfig.from_pretrained(
     id2label=id2label,
     label2id=label2id)
 
-downloadedModelFile = hf_hub_download(repo_id="zArabi/Persian-Sentiment-Analysis", filename="persianModel")
-loaded_model = torch.load(downloadedModelFile,map_location="cpu")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+path = 'HooshvareLab-bert-fa-base-uncased-3class.bin'
+downloadedModelDict = hf_hub_download(repo_id="zArabi/Persian-Sentiment-Analysis", filename=path)
+loaded_model = SentimentModel(config=config).to(device)
+loaded_model.load_state_dict(torch.load(downloadedModelDict, map_location="cpu"))
 
 
 tokenizer = BertTokenizer.from_pretrained(modelName)
 max_len=512
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 def predict(text):
   text = cleaning(text)