Update app.py

app.py

@@ -23,8 +23,8 @@ embeddings = torch.tensor(df['embedding'].tolist(), device=device)
 model = SentenceTransformer('all-MiniLM-L6-v2', device=device)
 
 # Load the ai model for response generation
-tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2-medium")
-model_response = AutoModelForCausalLM.from_pretrained("openai-community/gpt2-medium").to(device)
+tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
+model_response = AutoModelForCausalLM.from_pretrained("openai-community/gpt2").to(device)
 
 # Load the NLU model for intent detection
 nlu_model = AutoModelForSequenceClassification.from_pretrained("distilbert/distilbert-base-uncased-finetuned-sst-2-english").to(device)