Update app.py

app.py

@@ -1,33 +1,6 @@
 import gradio as gr
-from transformers import AutoModelForImageClassification, AutoProcessor
-import torch
 
 # Load the model and processor from Hugging Face
-model_name = "dima806/facial_age_image_detection"
-model = AutoModelForImageClassification.from_pretrained(model_name)
-processor = AutoProcessor.from_pretrained(model_name)
-
-# Define the prediction function
-def predict(image):
-    # Process the input image
-    inputs = processor(images=image, return_tensors="pt")
-    # Perform the prediction
-    with torch.no_grad():
-        outputs = model(**inputs)
-    
-    # Return the model's original outputs (e.g., logits or probabilities)
-    predictions = outputs.logits
-    
-    return predictions
-
-# Create Gradio interface
-iface = gr.Interface(
-    fn=predict,
-    inputs="image",
-    outputs="label",  # Use the model's original output type
-    title="Facial Age Prediction",
-    description="This application predicts your age from a facial image."
-)
-
+model = "dima806/facial_age_image_detection"
 # Launch the Gradio application
-iface.launch(share=True)
+model.launch(share=True)