Update app.py

app.py

@@ -37,7 +37,7 @@ def fine_tune_model(base_model_id, dataset):
     
     # Load pre-trained model and tokenizer
     model_name = "meta-llama/Meta-Llama-3.1-8B-Instruct"
-    model = AutoModelForCausalLM.from_pretrained(model_name)    
+    model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")    
     tokenizer = AutoTokenizer.from_pretrained(model_name)    
 
     # Preprocess the dataset
@@ -51,8 +51,6 @@ def fine_tune_model(base_model_id, dataset):
     train_dataset = dataset["train"].shuffle(seed=42).select(range(1000))  # Adjust the range as needed
     val_dataset = dataset["test"].shuffle(seed=42).select(range(100))  # Adjust the range as needed
 
-    torch.cuda.empty_cache()
-    
     # Set training arguments
     training_args = Seq2SeqTrainingArguments(
         output_dir="./results",