Saving and Loading a Model ========================== This section describes how to save and load models using R, Python, and Flow. In R and Python --------------- In R and Python, you can save a model locally or to HDFS using the ``h2o.saveModel`` (R) or ``h2o.save_model`` (Python) function . This function accepts the model object and the file path. If no path is specified, then the model will be saved to the current working directory. After the model is saved, you can load it using the ``h2o.loadModel`` (R) or ``h2o.load_model`` (Python) function. .. example-code:: .. code-block:: r # build the model model <- h2o.deeplearning(params) # save the model model_path <- h2o.saveModel(object=model, path=getwd(), force=TRUE) print(model_path) /tmp/mymodel/DeepLearning_model_R_1441838096933 # load the model saved_model <- h2o.loadModel(model_path) .. code-block:: python # build the model model = H2ODeepLearningEstimator(params) model.train(params) # save the model model_path = h2o.save_model(model=model, path="/tmp/mymodel", force=True) print model_path /tmp/mymodel/DeepLearning_model_python_1441838096933 # load the model saved_model = h2o.load_model(model_path) **Note**: When saving to HDFS, you must prepend the save directory with ``hdfs://``. For example: .. example-code:: .. code-block:: r # build the model model <- h2o.glm(model params) # save the model to HDFS hdfs_name_node <- "node-1" hdfs_tmp_dir <- "/tmp/runit” model_path <- sprintf("hdfs://%s%s", hdfs_name_node, hdfs_tmp_dir) h2o.saveModel(model, dir=model_path, name="mymodel") .. code-block:: python # build the model h2o_glm = H2OGeneralizedLinearEstimator(model params) h2o_glm.train(training params) # save the model to HDFS hdfs_name_node = "node-1" hdfs_model_path = sprintf("hdfs://%s%s", hdfs_name_node, hdfs_tmp_dir) new_model_path = h2o.save_model(h2o_glm, "hdfs://" + hdfs_name_node + "/" + hdfs_model_path) In Flow ------- The steps for saving and loading models in Flow are described in the **Using Flow - H2O's Web UI** section. Specifically, refer to `Exporting and Importing Models `__ for information about loading models into Flow.