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tsdocode
/
phobert-finetune-hatespeech

Text Classification
Transformers
PyTorch
Vietnamese
roberta
classification
Inference Endpoints
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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")
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Text Classification
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