Update app.py

app.py

@@ -102,28 +102,19 @@ def fine_tune_model(base_model_name, dataset_name):
     
     # Create trainer
     
-    #trainer = Seq2SeqTrainer(
-    #    model=model,
-    #    args=training_args,
-    #    train_dataset=train_dataset,
-    #    eval_dataset=test_dataset,
-    #    #compute_metrics=lambda pred: {"accuracy": torch.sum(pred.label_ids == pred.predictions.argmax(-1))},
-    #)
+    trainer = Seq2SeqTrainer(
+        model=model,
+        args=training_args,
+        train_dataset=train_dataset,
+        eval_dataset=test_dataset,
+        #compute_metrics=lambda pred: {"accuracy": torch.sum(pred.label_ids == pred.predictions.argmax(-1))},
+    )
 
     # Train model
     
-    #trainer.train()
-
-    # Save model and tokenizer to HF
+    trainer.train()
 
-    #login(token=os.environ["HF_TOKEN"])
-    
-    #api = HfApi()
-    #api.create_repo(repo_id=FT_MODEL_NAME)
-    #api.upload_folder(
-    #    folder_path="./output",
-    #    repo_id="Meta-Llama-3.1-8B-Instruct-text-to-sql"
-    #)
+    # Save tokenizer to HF
 
     tokenizer.push_to_hub("Meta-Llama-3.1-8B-Instruct-text-to-sql")