dev

app.py

@@ -23,7 +23,7 @@ model = AutoModelForSeq2SeqLM.from_pretrained('google/t5-efficient-tiny', num_la
 model = get_peft_model(model, lora_config)
 model.gradient_checkpointing_enable()   
 
-@spaces.GPU(duration=120)
+
 def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size, lr, grad):
     try:
         def compute_metrics(eval_pred):
@@ -141,6 +141,7 @@ def predict(text):
     return predictions.item()
 '''
 
+@spaces.GPU(duration=120)
 def run_train(dataset_name, hub_id, api_key, num_epochs, batch_size, lr, grad):
     result = fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size, lr, grad)
     return result