Error Loading Model in Tensorflow Java the model was trained and saved in tensorflow Python api

TensorFlow General Discussion
1

Java TensorFlow API Version - 2.4.1 , Python TensorFlow API version - 2.14

String pathString=“src/main/resource/ChatbotModel.zip”;
// try(SavedModelBundle model= SavedModelBundle.load(pathString, “serves”)){
// try( Tensor inputTensor= TFloat32.tensorOf());
// }

	SavedModelBundle model= SavedModelBundle.load(pathString,"serve");
	Session session=new Session(model.graph());

	
	//Tensor inpuTensor= session.getTensor
	
	//Tensor inputTensor= Tensor.create("Hows you?",String.class);
	
	Tensor inputTensor=TString.scalarOf("what is your name");
	Tensor outputTensor = model.session().runner()
			.feed("prediction_input",inputTensor)
			.fetch("response_tag")
			.run().get(0);


	String outputString = outputTensor.toString();
	System.out.println("Answer is: "+ outputString);

This is my Code when I tried to load a trained model on my machine only in Java i got Error :

Converting GraphDef to Graph has failed with an error: ‘Op type not registered ‘DisableCopyOnRead’ in binary running on IN-UJJWALSENGAR. Make sure the Op and Kernel are registered in the binary running in this process. Note that if you are loading a saved graph which used ops from tf.contrib, accessing (e.g.) tf.contrib.resampler should be done before importing the graph, as contrib ops are lazily registered when the module is first accessed.’ The binary trying to import the GraphDef was built when GraphDef version was 561. The GraphDef was produced by a binary built when GraphDef version was 1575. The difference between these versions is larger than TensorFlow’s forward compatibility guarantee, and might be the root cause for failing to import the GraphDef.

If anyone can help me with this I read on blogpost that Tensorflow API 2.00 has forward compatibility for all the versions, even so This error persist