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| from transformers import ( # pylint: disable=import-error | |
| AutoTokenizer, | |
| AutoModelForSequenceClassification, | |
| AutoModelForCausalLM, | |
| pipeline | |
| ) | |
| import logging | |
| class SIDetector(object): | |
| def __init__(self): | |
| self.classifier = pipeline("sentiment-analysis", model="sentinet/suicidality") | |
| def forward(self, text: str): | |
| output = self.classifier(text)[0] | |
| suicidal = True if output['label'] == 'LABEL_1' else False | |
| confidence = output['score'] | |
| logging.info(f"Suicidal: {suicidal}, Confidence: {confidence}") | |
| return suicidal, confidence |