Update app.py

app.py

@@ -13,10 +13,6 @@ model = AutoModelForCausalLM.from_pretrained("SivaResearch/tinyllama-Siv-v2")
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 model = model.to(device)
 
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 # Defining a custom stopping criteria class for the model's text generation.
 class StopOnTokens(StoppingCriteria):
     def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool: