Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load your image captioning model from Hugging Face
+model_name = "Mayada/AIC-transformer"  # Update this with your model path
+captioner = pipeline("image-to-text", model=model_name)
+
+# Define a function to generate a caption from an image
+def generate_caption(image):
+    result = captioner(image)
+    return result[0]['generated_text']
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=generate_caption,  # Function to process image and return caption
+    inputs=gr.inputs.Image(type="pil"),  # Accept image input
+    outputs="text",  # Output the caption as text
+    title="AIC-transformer-2023",  # Title for your interface
+    description="Description",  # Description for users
+)
+
+# Launch the Gradio interface
+interface.launch()
+