deve

app.py

@@ -83,9 +83,9 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
             save_total_limit=3, 
         )
         # Check if a checkpoint exists and load it
-        if os.path.exists(training_args.output_dir) and os.listdir(training_args.output_dir):
-            print("Loading model from checkpoint...")
-            model = AutoModelForSeq2SeqLM.from_pretrained(training_args.output_dir)        
+        #if os.path.exists(training_args.output_dir) and os.listdir(training_args.output_dir):
+            #print("Loading model from checkpoint...")
+            #model = AutoModelForSeq2SeqLM.from_pretrained(training_args.output_dir)        
     
         tokenizer = AutoTokenizer.from_pretrained('google/t5-efficient-tiny-nh8')