Create app.py

app.py

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+from transformers import pipeline
+import gradio as gr
+from PIL import Image
+
+# Load the image captioning pipeline
+pipe = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
+
+def generate_caption(image):
+    # Generate a caption for the image
+    captions = pipe(image)
+    return captions[0]['generated_text']
+
+# Create a Gradio interface for image captioning
+demo = gr.Interface(
+    fn=generate_caption,
+    inputs=gr.Image(type="pil", label="Upload an Image"),
+    outputs=gr.Textbox(label="Generated Caption"),
+    title="Image Caption Generator",
+    description="Upload an image to generate a caption using the BLIP model."
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    demo.launch(share=True)