XAI


data_config = {
    "tags": ["Training"],
    "feature_include": feature_include # data used for training/generating synthetic data
}
hyper_params = {
    "epochs": 2,          # epochs are no of iteration of data into model (more the better, but longer) # Max 100 supported
    "test_ratio": 0.2     # Data used for training/generating synthetic data. how much to keep aside for testing
}

project.train_synthetic_model(
    model_name='CTGAN',                    # CTGAN / GPT2 , models are avaialable
    data_config=data_config,
    hyper_params=hyper_params,
    # instance_type = "2xlargeT4"  #pass instance_type for dedicated reesources , defaults to shared resources
    )

‍

Retrieve available synthetic custom servers provided by AryaXAI library:


aryaxai.available_synthetic_custom_servers()

‍

Fetch trained models:


project.synthetic_models()

Train synthetic model:


project.train_synthetic_model()

‍

Help function to train the synthetic model:


help(project.train_synthetic_model)

‍

Define parameters for your synthetic model:


data_config = {
    "tags": ["Training"],
    "feature_include": feature_include # data used for training/generating synthetic data
}
hyper_params = {
    "epochs": 2,          # epochs are no of iteration of data into model (more the better, but longer) # Max 100 supported
    "test_ratio": 0.2     # Data used for training/generating synthetic data. how much to keep aside for testing
}

project.train_synthetic_model(
    model_name='CTGAN',                    # CTGAN / GPT2 , models are avaialable
    data_config=data_config,
    hyper_params=hyper_params,
    # instance_type = "2xlargeT4"  #pass instance_type for dedicated reesources , defaults to shared resources
    )

‍

Retrieve available synthetic custom servers provided by AryaXAI library:


aryaxai.available_synthetic_custom_servers()

‍

Fetch trained models:


project.synthetic_models()

Example H2

Example H3