Update app.py

app.py

@@ -16,10 +16,10 @@ model = AutoModelForCausalLM.from_pretrained("google/gemma-2b", token=HF_TOKEN)
 model = PeftModel.from_pretrained(model, "pranjalpandey/gemma-open-instruct")
 # model = AutoPeftModelForCausalLM.from_pretrained("pranjalpandey/llama-7b-finetuned-dialogue-summarizer")
 tokenizer = AutoTokenizer.from_pretrained("pranjalpandey/gemma-open-instruct", token=HF_TOKEN)
-model = model.to("cuda")
+# model = model.to("cuda")
 
 def response(prompt):
-  inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+  inputs = tokenizer(prompt, return_tensors="pt")
   outputs = model.generate(input_ids=inputs["input_ids"], max_new_tokens=100)
   return tokenizer.batch_decode(outputs.detach().cpu().numpy(), skip_special_tokens=True)[0].split("# Response:")[1].strip()