deeppavlov.models.relation_extraction¶
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class
deeppavlov.models.relation_extraction.relation_extraction_bert.
REBertModel
(n_classes: int, num_ner_tags: int, pretrained_bert: Optional[str] = None, return_probas: bool = False, threshold: Optional[float] = None, **kwargs)[source]¶ -
__init__
(n_classes: int, num_ner_tags: int, pretrained_bert: Optional[str] = None, return_probas: bool = False, threshold: Optional[float] = None, **kwargs) → None[source]¶ Transformer-based model on PyTorch for relation extraction. It predicts a relation hold between entities in a text sample (one or several sentences). :param n_classes: number of output classes :param num_ner_tags: number of NER tags :param pretrained_bert: key title of pretrained Bert model (e.g. “bert-base-uncased”) :param return_probas: set this to True if you need the probabilities instead of raw answers :param threshold: manually set value for defining the positively predicted classes (instead of adaptive one)
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