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· 4 min read

TensorFlow models are saved in the protocol buffer format, which is an efficient way of storing and transporting data. I first heard and used it when I worked at Popsa where we used them to speed network requests between mobile apps and the backend. I then realised TensorFlow also uses this format to store models, including the weights and metadata. Popsa had a github repo specifically used to design and agree upon the interface between the backend and the mobile applications. gRPC also uses protocol buffers as the format. gRPC also uses protocol buffers as its format, by default. You can generate the classes to create, serialize and deserialize these objects in your preferred language with the protobuf compiler, protoc.