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phobert-finetune-hatespeech
tsdocode/phobert-finetune-hatespeech
phobert-finetune-hatespeech is a text classification model from tsdocode. Use it when you need a label for a piece of text. It is set up for transformers.
- VLSP2019: Hate Speech Detection on Social Networks Dataset - ViHSD: Vietnamese Hate Speech Detection dataset
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- May 7, 2022
- Updated
- May 7, 2022
- SHA
- ba304921
Try a prompt
Model card
From the Hugging Face model README
PhoBert finetuned version for hate speech detection
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")
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- vi
- Created
- May 7, 2022
- Updated
- May 7, 2022