:py:mod:`medcat.utils.relation_extraction.bert.model`
=====================================================

.. py:module:: medcat.utils.relation_extraction.bert.model


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   medcat.utils.relation_extraction.bert.model.BertModel_RelationExtraction




.. py:class:: BertModel_RelationExtraction(pretrained_model_name_or_path, relcat_config, model_config)


   Bases: :py:obj:`medcat.utils.relation_extraction.models.BaseModel_RelationExtraction`

   BertModel class for RelCAT


   .. py:attribute:: name
      :value: 'bertmodel_relcat'

      

   .. py:attribute:: log

      

   .. py:method:: __init__(pretrained_model_name_or_path, relcat_config, model_config)

      Class to hold the BERT model + model_config

      :param pretrained_model_name_or_path: path to load the model from,
                                            this can be a HF model i.e: "bert-base-uncased", if left empty, it is normally assumed that a model is loaded from 'model.dat'
                                            using the RelCAT.load() method. So if you are initializing/training a model from scratch be sure to base it on some model.
      :type pretrained_model_name_or_path: str
      :param relcat_config: relcat config.
      :type relcat_config: ConfigRelCAT
      :param model_config: HF bert config for model.
      :type model_config: Union[BaseConfig_RelationExtraction | BertConfig_RelationExtraction]


   .. py:method:: load(pretrained_model_name_or_path, relcat_config, model_config, **kwargs)
      :classmethod:

      Load the model from the given path

      :param pretrained_model_name_or_path: path to load the model from.
      :type pretrained_model_name_or_path: str
      :param relcat_config: relcat config.
      :type relcat_config: ConfigRelCAT
      :param model_config: The model-specific config.
      :type model_config: BaseConfig_RelationExtraction

      :returns: **BaseModel_RelationExtraction** -- The loaded model.