detector_benchmark.detector.bert_detector¶
Classes¶
Module Contents¶
- class detector_benchmark.detector.bert_detector.BertDetector(model: torch.nn.Module, tokenizer: transformers.PreTrainedTokenizerBase, device: str)¶
Bases:
detector_benchmark.detector.detector.Detector- model¶
- tokenizer¶
- device¶
- detect(texts: list[str], batch_size: int, detection_threshold: float = 0.0) tuple[list[int], list[float], list[int]]¶
Detect the if the texts given as input are AI-generated (label 1) or human-written (label 0). Returns the predicted lables with argmax, the logits of the positive class and the predicted labels with the given detection threshold instead of the argmax.
Parameters:¶
- texts: list[str]
The texts to detect
- batch_size: int
The batch size to use for detection
- detection_threshold: float
The threshold to use for detection. Default is 0.0.
Returns:¶
- tuple[list[int], list[float], list[int]]
The predicted labels with argmax, the logits of the positive class and the predicted labels with the given detection threshold instead of the argmax.