# Hate speech detection

MetaHateBERT is a text classification model based on the BERT architecture, specifically designed for detecting hate speech.

ViSoBERT is the first monolingual pre-trained language model specifically designed for Vietnamese social media text, based on the XLM-R architecture, and has demonstrated excellent performance in various Vietnamese social media tasks.

Based on the XLM-Roberta-base model, continuously pre-trained on Arabic Twitter corpus and fine-tuned on the XNLI Arabic dataset for zero-shot text classification.

Based on the XLM-Roberta-base model, it underwent continuous pre-training on a large multilingual Twitter corpus and was fine-tuned on the Chinese XNLI dataset, focusing on zero-shot text classification in Chinese.

Based on the XLM-Roberta-base model, continuously pretrained on a multilingual Twitter corpus and fine-tuned on the French XNLI dataset for zero-shot text classification

A model fine-tuned based on bert-base-uncased for identifying hateful meme text content

RoBERTuito is a language model pre-trained specifically for Spanish social media text, trained on 500 million tweets, and excels in various Spanish social media text tasks.

Hate speech detection model fine-tuned on distilbert-base-uncased, trained on tweet_eval dataset

This is a binary classification model trained via AutoNLP for detecting hate speech content in text.

A hate speech detection model fine-tuned on distilbert-base-uncased, trained on the tweet_eval dataset

A lightweight model based on DistilBERT for detecting hate speech and offensive content in text

A lightweight model based on DistilBERT for detecting hate speech and offensive content in text

Hate speech detection model fine-tuned based on distilbert-base-uncased

This model is a fine-tuned version of distilbert-base-uncased, designed for classifying hate speech and offensive content.

A lightweight model based on DistilBERT, fine-tuned for hate speech and offensive language detection tasks

This model is designed to detect hate speech in Indonesian, fine-tuned based on multilingual BERT and trained exclusively with Indonesian data.

This model is used to detect hate speech in Portuguese, fine-tuned from a multilingual BERT model as a monolingual model.

A BERT-based text classification model for detecting hate speech and offensive content, with rationale prediction capability

A lightweight model based on DistilBERT, fine-tuned for hate speech and offensive language detection tasks

A lightweight model based on DistilBERT for detecting hate speech and offensive content in text

Hate speech/offensive language detection model fine-tuned based on DistilBERT-base-uncased

HateXplain is a text classification model for detecting hate speech, offensive content, and normal content, trained on data from Gab and Twitter, with enhanced performance through human-annotated rationale.