Update app.py

app.py

@@ -66,8 +66,8 @@ mod.bind(for_training=False, data_shapes=[('data_0', (1,3,224,224))],
          label_shapes=mod._label_shapes)
 mod.set_params(arg_params, aux_params, allow_missing=True, allow_extra=True)
 
-title="SqueezeNet"
-description="SqueezeNet is a small CNN which achieves AlexNet level accuracy on ImageNet with 50x fewer parameters. SqueezeNet requires less communication across servers during distributed training, less bandwidth to export a new model from the cloud to an autonomous car and more feasible to deploy on FPGAs and other hardware with limited memory."
+title="AlexNet"
+description="AlexNet is the name of a convolutional neural network for classification, which competed in the ImageNet Large Scale Visual Recognition Challenge in 2012."
 
 examples=[['catonnx.jpg']]
 gr.Interface(predict,gr.inputs.Image(type='filepath'),"label",title=title,description=description,examples=examples).launch(enable_queue=True)