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Upload Models in AryaXAI

Before uploading a model, ensure that the corresponding features have already been uploaded through the data upload process.

Select the tag in which your model is trained on. Also, you can define the test data when you are uploading the model


project.upload_model(model_path='/content/xgb_sample_model.pkl',
                     model_name = 'XgbCustom',
                     model_data_tags = ['Training'],
                     model_type='Xgboost',
                     model_architecture='machine_learning')

Help on method upload_model in module aryaxai.core.project


help(project.upload_model)

Following are the models that you can upload to AryaXAI:

NOTE:Deep Learning is not available at the moment. Only use ML.


project.upload_model_types()

{'model_architecture': {'machine_learning': ['Xgboost',
   'Lgboost',
   'CatBoost',
   'Random_forest',
   'Linear_Regression',
   'Logistic_Regression',
   'Gaussian_NaiveBayes',
   'SGD'],
  'deep_learning': ['tensorflow', 'pytorch']},
 'prediction_type': ['classification', 'regression']}
 

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


project.models()

Delete uploaded file


project.delete_file('file name')