About saved models

[eishwezin20]

does anyone know difference between ".h5", ".hdf5", ".model". I am using tensorflow.

[Mattral]

When using TensorFlow and Keras, you'll typically encounter the ".h5" file extension for saving and loading machine learning models. Here's the difference between ".h5", ".hdf5", and ".model" in the context of TensorFlow and Keras:

1. ".h5" or ".hdf5":

   • These extensions are used to save and load machine learning models in a hierarchical data format (HDF5) using libraries like TensorFlow and Keras.
   • ".h5" files are a common choice for saving neural network models and their associated weights. You can use functions like model.save("model.h5") to save your model and tf.keras.models.load_model("model.h5") to load it back later.
   • The ".h5" or ".hdf5" format is widely supported, efficient for storing large models, and is the recommended choice for model persistence in TensorFlow and Keras.

2. ".model":

   • The ".model" extension is not a standard format for saving models in TensorFlow or Keras. Instead, these libraries primarily use ".h5" or ".hdf5" for model serialization.
   • If you encounter a ".model" file, it's likely a custom or non-standard format specific to a particular application or library. To work with such files, you would need to refer to the documentation or source code of the software that generated them to understand how to load and use the models stored within.

In summary, when working with TensorFlow and Keras, you should use the ".h5" or ".hdf5" extension for saving and loading models. These formats are well-established, supported, and provide an efficient way to store and retrieve your machine learning models. The ".model" extension is not a standard choice for model persistence in these libraries.

[eishwezin20]

Thanks