edited app file

app.py

@@ -4,8 +4,9 @@ from transformers import Trainer, TrainingArguments
 from os.path import dirname
 
 
-my_model = GPT2LMHeadModel.from_pretrained(f'{dirname(__file__)}/repo')
-my_tokenizer = GPT2Tokenizer.from_pretrained(f'{dirname(__file__)}/repo')
+model_output_path="/model_dir"
+my_model = GPT2LMHeadModel.from_pretrained(model_output_path)
+my_tokenizer = GPT2Tokenizer.from_pretrained(model_output_path)
 
 def predict(prompt):
   response = generate_response(my_model, my_tokenizer, prompt)