Upload Models in AryaXAI
Add DL Model in Tabular data:
To upload a deep learning model designed for tabular data, use the following function:
project.upload_model(model_path='/content/dl model.h5',
model_name = 'DL model',
model_data_tags = ['training'],
model_test_tags = ['training'],
model_type='tensorflow',
model_architecture='deep_learning',
instance_type='small',
explainability_method=['shap'],
feature_list=['duration',
'credit_amount',
'installment_rate'])
Add DL Model in Tabular data:
To upload a deep learning model designed for image data, use the following function:
project.upload_model(model_path='/content/cifar10epoch100 (Copy).h5',
model_name = 'cifar2',
model_data_tags = ['testing'],
model_test_tags = ['testing'],
model_type='tensorflow',
model_architecture='deep_learning',
instance_type='small')
Add ML Model:
NOTE:To upload model we first need to ensure the features going into model are already uploaded using data upload
Select the tag in which you have your model input data:
project.upload_model(model_path='/content/xgb_sample_model.pkl',
model_name = 'XgbCustom',
model_data_tags = ['training'],
model_test_tags = ['training'],
model_type='Xgboost',
model_architecture='machine_learning',
instance_type='small')
Help function to upload a machine learning model:
help(project.upload_model)
View uploaded model Information
To see the uploaded model info., use the following function:
help(project.upload_model)
NOTE: If you encounter an error, please ensure that the columns in the files you uploaded match those used in your model. We use your model settings to validate that the data in these tags is consistent. The framework will only proceed with adding the model if all features are available.
View uploaded model info
Delete uploaded file
project.delete_file('file name')
Upload Models in AryaXAI
Add DL Model in Tabular data:
To upload a deep learning model designed for tabular data, use the following function:
project.upload_model(model_path='/content/dl model.h5',
model_name = 'DL model',
model_data_tags = ['training'],
model_test_tags = ['training'],
model_type='tensorflow',
model_architecture='deep_learning',
instance_type='small',
explainability_method=['shap'],
feature_list=['duration',
'credit_amount',
'installment_rate'])
Add DL Model in Tabular data:
To upload a deep learning model designed for image data, use the following function:
project.upload_model(model_path='/content/cifar10epoch100 (Copy).h5',
model_name = 'cifar2',
model_data_tags = ['testing'],
model_test_tags = ['testing'],
model_type='tensorflow',
model_architecture='deep_learning',
instance_type='small')
Add ML Model:
NOTE:To upload model we first need to ensure the features going into model are already uploaded using data upload
Select the tag in which you have your model input data:
project.upload_model(model_path='/content/xgb_sample_model.pkl',
model_name = 'XgbCustom',
model_data_tags = ['training'],
model_test_tags = ['training'],
model_type='Xgboost',
model_architecture='machine_learning',
instance_type='small')
Help function to upload a machine learning model:
help(project.upload_model)
View uploaded model Information
To see the uploaded model info., use the following function:
help(project.upload_model)
NOTE: If you encounter an error, please ensure that the columns in the files you uploaded match those used in your model. We use your model settings to validate that the data in these tags is consistent. The framework will only proceed with adding the model if all features are available.
View uploaded model info
Delete uploaded file
project.delete_file('file name')
