This model is based on a BERT model trained with a few bullying detection datasets. It is trained exclusively in the Indonesian language.

from transformers import BertTokenizer, AutoModelForSequenceClassification

model_path = 'kairaamilanii/IndoBERT-Bullying-Classifier'
tokenizer = BertTokenizer.from_pretrained(model_path)
model = AutoModelForSequenceClassification.from_pretrained(model_path)

text = "KOK JELEK BANGET SIH" # Example text for prediction

inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)
    predicted_class = torch.argmax(outputs.logits, dim=-1).item()
print(f"Predicted class: {predicted_class}")

if predicted_class == 1:
    print("Prediction: Bullying")
else:
    print("Prediction: Non-bullying")

example output:

[{'Predicted class': 1, 'Prediction': Bullying}]
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