deve

app.py

@@ -107,7 +107,7 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
             # Assuming 'text' is the input and 'target' is the expected output
             model_inputs = tokenizer(
                 examples['text'], 
-                #max_length=max_length,  # Set to None for dynamic padding
+                max_length=max_length,  # Set to None for dynamic padding
                 truncation=True,
                 padding='max_length',
                 #return_tensors='pt',
@@ -117,7 +117,7 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
             # Setup the decoder input IDs (shifted right)
             labels = tokenizer(
                 examples['target'], 
-                #max_length=128,  # Set to None for dynamic padding
+                max_length=128,  # Set to None for dynamic padding
                 truncation=True,
                 padding='max_length',
                 #text_target=examples['target'],