Update app.py

app.py

@@ -3,15 +3,15 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 import gradio as gr
 
 # Adjust this to your model ID
-model_id = "meta-llama/Meta-Llama-3-8B-Instruct"
-peft_model_id = "decision-oaif/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0"
+model_id = "meta-llama/Meta-Llama-3.1-8B-Instruct"
+#peft_model_id = "decision-oaif/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0"
 # Load model with device map and dtype
 model = AutoModelForCausalLM.from_pretrained(
     model_id,
     torch_dtype=torch.bfloat16,
     device_map="auto"
 )
-model.load_adapter(peft_model_id)
+#model.load_adapter(peft_model_id)
 
 # Load tokenizer and set truncation and padding
 tokenizer = AutoTokenizer.from_pretrained(model_id, truncation=True, padding=True)