tsdocode/phobert-finetune-hatespeech

PhoBert

Dataset

• VLSP2019: Hate Speech Detection on Social Networks Dataset
• ViHSD: Vietnamese Hate Speech Detection dataset

Class name

• LABEL_0 : Normal
• LABEL_1 : OFFENSIVE
• LABEL_2 : HATE

Usage example with TextClassificationPipeline

from transformers import AutoModelForSequenceClassification, AutoTokenizer, TextClassificationPipeline


model = AutoModelForSequenceClassification.from_pretrained("tsdocode/phobert-finetune-hatespeech", num_labels=3)
tokenizer = AutoTokenizer.from_pretrained("tsdocode/phobert-finetune-hatespeech")


pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
# outputs a list of dicts like [[{'label': 'NEGATIVE', 'score': 0.0001223755971295759},  {'label': 'POSITIVE', 'score': 0.9998776316642761}]]
pipe("đồ ngu")