explabox.ingestibles.model

Functions to import models from the genbase library.

explabox.ingestibles.model.import_model(model, environment=None, train='train', label_map=None)

Import a model from file or from a Python object.

Examples

Make a scikit-learn text classifier and train it on SST2

>>> from genbase import import_data, import_model
>>> from datasets import load_dataset
>>> ds = import_data(load_dataset('glue', 'sst2'), data_cols='sentence', label_cols='label')
>>> from sklearn.pipeline import Pipeline
>>> from sklearn.naive_bayes import MultinomialNB
>>> from sklearn.feature_extraction.text import TfidfVectorizer
>>> pipeline = Pipeline([('tfidf', TfidfVectorizer()),
...                      ('clf', MultinomialNB())])
>>> import_model(pipeline, ds, train='train')
Load a pretrained ONNX model downloaded from

https://github.com/mpbron/instancelib-onnx/blob/main/example_models/data-model.onnx

>>> from genbase import import_model
>>> import_model('data-model.onnx', label_map={0: 'Bedrijfsnieuws', 1: 'Games', 2: 'Smartphones'})
Parameters:

  • model – Model or path to model to import.

  • environment (Optional[Environment], optional) – Environment corresponding to model (with dataset and ground-truth labels), used for importing models and/or training them.

  • train (Union[int, float, str, InstanceProvider], optional) – Train split size, name in environment or provider. Defaults to ‘train’.

  • label_map (Optional[Dict[LT, LT]], optional) – Conversion of label IDs to named labels. Defaults to None.

Raises:

  • ImportError – Unable to import model or file.

  • NotImplementedError – Type of model is not yet supported.

Returns:

Instancelib wrapped model.

Return type:

AbstractClassifier