readme: ---
  language:
  - vi
  tags:
  - classification
  widget:
  - text: "Xấu vcl"
    example_title: "Công kích"
  - text: "Đồ ngu"
    example_title: "Thù ghét"
  - text: "Xin chào chúc một ngày tốt lành"
    example_title: "Normal"
  
  ---
  
  ## [PhoBert](https://huggingface.co/vinai/phobert-base/tree/main) finetuned version for hate speech detection
  
  ## Dataset
  - [**VLSP2019**](https://github.com/sonlam1102/vihsd): Hate Speech Detection on Social Networks Dataset
  - [**ViHSD**](https://vlsp.org.vn/vlsp2019/eval/hsd): Vietnamese Hate Speech Detection dataset
  
  ## Class name
  - LABEL_0 : **Normal**
  - LABEL_1 : **OFFENSIVE**
  - LABEL_2 : **HATE**
  
  
  ## Usage example with **TextClassificationPipeline**
  ```python
  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")
  
  ```