update model weight path

app.py

@@ -4,7 +4,6 @@ from torchtext.data.utils import get_tokenizer
 import numpy as np
 import subprocess
 
-
 from huggingface_hub import hf_hub_download
 from transformer import Transformer
 
@@ -30,7 +29,7 @@ src_vocab = len(vocab)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model = Transformer(len(vocab), len(vocab), d_model, N, heads).to(device)
 model.load_state_dict(torch.load(hf_hub_download(repo_id="nickgardner/chatbot",
-                                      filename="alpaca_train_380_epoch.pt"), map_location=device))
+                                      filename="alpaca_train_400_epoch.pt"), map_location=device))
 model.eval()
 
 def respond(custom_string):