ViHateT5: Enhancing Hate Speech Detection in Vietnamese with A Unified Text-to-Text Transformer Model | ACL'2024 (Findings)
Disclaimer: This paper contains examples from actual content on social media platforms that could be considered toxic and offensive.
ViHateT5-HSD is the fine-tuned model of ViHateT5 on multiple Vietnamese hate speech detection benchmark datasets.
The architecture and experimental results of ViHateT5 can be found in the paper:
@inproceedings{thanh-nguyen-2024-vihatet5,
title = "{V}i{H}ate{T}5: Enhancing Hate Speech Detection in {V}ietnamese With a Unified Text-to-Text Transformer Model",
author = "Thanh Nguyen, Luan",
editor = "Ku, Lun-Wei and Martins, Andre and Srikumar, Vivek",
booktitle = "Findings of the Association for Computational Linguistics ACL 2024",
month = aug,
year = "2024",
address = "Bangkok, Thailand and virtual meeting",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-acl.355",
pages = "5948--5961"
}
The pre-training dataset named VOZ-HSD is available at HERE.
Kindly CITE our paper if you use ViHateT5-HSD to generate published results or integrate it into other software.
Example usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("tarudesu/ViHateT5-base-HSD")
model = AutoModelForSeq2SeqLM.from_pretrained("tarudesu/ViHateT5-base-HSD")
def generate_output(input_text, prefix):
# Add prefix
prefixed_input_text = prefix + ': ' + input_text
# Tokenize input text
input_ids = tokenizer.encode(prefixed_input_text, return_tensors="pt")
# Generate output
output_ids = model.generate(input_ids, max_length=256)
# Decode the generated output
output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
return output_text
sample = 'Tôi ghét bạn vl luôn!'
prefix = 'hate-spans-detection' # Choose 1 from 3 prefixes ['hate-speech-detection', 'toxic-speech-detection', 'hate-spans-detection']
result = generate_output(sample, prefix)
print('Result: ', result)
Please feel free to contact us by email luannt@uit.edu.vn if you have any further information!