python-kerasHow do I save a Keras model in Python?
Saving a Keras model in Python is relatively simple and can be done in a few lines of code. To save a model, we use the model.save()
function. This function takes in a file path to save the model to. For example:
model.save('model.h5')
This will save the model as an HDF5 file called model.h5
.
The model.save()
function has several optional parameters that can be used to customize the saving process. For example, the include_optimizer
parameter can be set to True
to save the state of the optimizer used to train the model, allowing the model to resume training where it left off.
The following is a list of the parts of the code and a brief explanation of each:
model.save()
: This is the function used to save the model.model.h5
: This is the file path to save the model to.include_optimizer
: This is an optional parameter that can be set toTrue
to save the state of the optimizer used to train the model.
For more information on saving Keras models, please see the Keras documentation.
More of Python Keras
- How can I improve the validation accuracy of my Keras model using Python?
- How can I use XGBoost, Python and Keras together to build a machine learning model?
- How do I use Python Keras to create a Zoom application?
- How do I use the model.fit function in Python Keras?
- How can I use word2vec and Keras to develop a machine learning model in Python?
- How can I install the python module tensorflow.keras in R?
- How can I resolve the issue of Python module Tensorflow.keras not being found?
- How can I use Python and Keras to create a Variational Autoencoder (VAE)?
- How do I plot a model using Python and Keras?
- How do I install the Python Keras .whl file?
See more codes...