Credits to original space

app.py

@@ -32,7 +32,7 @@ image = gr.inputs.Image(type="pil")
 label = gr.outputs.Label(num_top_classes=5)
 examples = [["cats.jpg"], ["dog.jpg"]]
 title = "Interactive demo: Perceiver for image classification"
-description = "Demo for classifying images with Perceiver IO. To use it, simply upload an image or use the example images below and click 'submit' to let the model predict the 5 most probable ImageNet classes. Results will show up in a few seconds."
+description = "Demo for classifying images with Perceiver IO. To use it, simply upload an image or use the example images below and click 'submit' to let the model predict the 5 most probable ImageNet classes. Results will show up in a few seconds. This is based on this space: This space is based on: https://huggingface.co/spaces/nielsr/perceiver-image-classification, image net labels are machine translated from english to spanish."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2107.14795'>Perceiver IO: A General Architecture for Structured Inputs & Outputs</a> | <a href='https://deepmind.com/blog/article/building-architectures-that-can-handle-the-worlds-data/'>Official blog</a></p>"
 
 gr.Interface(fn=classify_image, inputs=image, outputs=label, title=title, description=description, examples=examples, enable_queue=True).launch(debug=True)