gradio fix

app.py

@@ -48,14 +48,14 @@ def fine_tune_model(model_name, dataset_name, hub_id, num_epochs, batch_size, lr
     trainer.train()
     trainer.push_to_hub(commit_message="Training complete!")
     return 'DONE!'#model
-
+'''
 # Define Gradio interface
 def predict(text):
     inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
     outputs = model(inputs)
     predictions = outputs.logits.argmax(dim=-1)
     return "Positive" if predictions.item() == 1 else "Negative"
-
+'''
 # Create Gradio interface
 iface = gr.Interface(
     fn=fine_tune_model,
@@ -65,7 +65,6 @@ iface = gr.Interface(
         gr.inputs.Textbox(label="HF hub to push to after training"),
         gr.inputs.Slider(minimum=1, maximum=10, default=3, label="Number of Epochs"),
         gr.inputs.Slider(minimum=1, maximum=16, default=4, label="Batch Size"),
-        gr.inputs.Slider(minimum=1, maximum=16, default=4, label="Batch Size"),
         gr.inputs.Slider(minimum=1, maximum=1000, default=50, label="Learning Rate (e-6)"),
         gr.inputs.Slider(minimum=1, maximum=100, default=1, label="Gradient accumulation (e-1)"), 
     ],