Update app.py

app.py

@@ -7,7 +7,14 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 tokenizer = AutoTokenizer.from_pretrained("VietAI/vit5-base")
 model = AutoModelForSeq2SeqLM.from_pretrained("VietAI/vit5-base")
 model_file = hf_hub_download(repo_id="tuongvxx1/medBot", filename="medicalBot_ver4.pth")
-model.load_state_dict(torch.load(model_file, map_location=torch.device('cpu')))
+
+state_dict = torch.load('medicalBot_ver4.pth', map_location=torch.device('cpu'))
+from collections import OrderedDict
+new_state_dict = OrderedDict()
+for k, v in state_dict.items():
+    name = k.replace('module.', '')
+    new_state_dict[name] = v
+model.load_state_dict(new_state_dict)
 model.to(device)
 
 def generate_answer(question, model, tokenizer, device):