init

app.py

@@ -67,15 +67,15 @@ def predict(text):
 try:
     
     iface = gr.Interface(
-        fine_tune_model,
+        fn=fine_tune_model,
         inputs=[
-            gr.inputs.Textbox(label="Model Name (e.g., 'google/t5-efficient-tiny-nh8')"),
-            gr.inputs.Textbox(label="Dataset Name (e.g., 'imdb')"),
-            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=100, default=50, label="Learning Rate (e-5)"),
-            gr.inputs.Slider(minimum=1, maximum=100, default=1, label="Gradient accumulation (e-1)"), 
+            gr.Textbox(label="Model Name (e.g., 'google/t5-efficient-tiny-nh8')"),
+            gr.Textbox(label="Dataset Name (e.g., 'imdb')"),
+            gr.Textbox(label="HF hub to push to after training"),
+            gr.Slider(minimum=1, maximum=10, default=3, label="Number of Epochs"),
+            gr.Slider(minimum=1, maximum=16, default=4, label="Batch Size"),
+            gr.Slider(minimum=1, maximum=100, default=50, label="Learning Rate (e-5)"),
+            gr.Slider(minimum=1, maximum=100, default=1, label="Gradient accumulation (e-1)"), 
         ],
         outputs="text",
         title="Fine-Tune Hugging Face Model",