Update app.py

app.py

@@ -64,11 +64,7 @@ emotion_prediction_tokenizer = AutoTokenizer.from_pretrained("bhadresh-savani/di
 response_model_name = "gpt2-xl"
 response_tokenizer = AutoTokenizer.from_pretrained(response_model_name)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-with init_empty_weights():
-    response_model = AutoModelForCausalLM.from_pretrained(response_model_name)
-    response_model.tie_weights()
-response_model.to(device)
+response_model = load_checkpoint_and_dispatch(AutoModelForCausalLM, response_model_name, device_map="auto")
 
 # Set the pad token
 response_tokenizer.pad_token = response_tokenizer.eos_token
@@ -102,6 +98,7 @@ def save_historical_data(historical_data, file_path=emotion_history_file):
 
 emotion_history = load_historical_data()
 
+
 def update_emotion(emotion, percentage, intensity):
     emotions[emotion]['percentage'] += percentage
     emotions[emotion]['intensity'] = intensity