Fast text toxicity classification model
-
Updated
May 31, 2024 - Python
Fast text toxicity classification model
In this project we have tried to do multi-label hate-speech classification in Bengali and Hindi language using fill-mask transformer models.
Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at contact@unitary.ai.
A supervised learning based tool to identify toxic code review comments
Atividade prática de Redes Neurais
Applies probability based bag-of-words model for toxicity classification of social media texts
AntiToxicBot is a bot that detects toxics in a chat using Data Science and Machine Learning technologies. The bot will warn admins about toxic users. Also, the admin can allow the bot to ban toxics.
Classifying users on social media, using text embeddings from OpenAI and others
Genshin Impact Twitter Toxicity Research
Projects concerning LLMs, prompting, NLP, webscraping, data aquisition and dataset analysis.
This repository makes available a new dataset for toxicity detection in Brazilian Portuguese from the work accepted by the 16th International Conference on Computational Processing of Portuguese (PROPOR 2024). The data collected is from the most popular Brazilian subreddits in 2022.
Full stack application for annotating video game matches. Used for https://github.com/TheBv/toxic-video-games-gnn
A web-app to identify toxic comments in a youtube channel and delete them.
A revolutionary AI-powered platform to help you solve doubts instantly, make learning easy, and achieve academic success.
A Simple PoC (Proof of Concept) of Hate speech (Toxic comment) Detector API Server
Machine learning pipeline for predicting molecular toxicity.
Module for predicting toxicity messages in Russian and English
Toxformer is an attempt at using transformers to predict the toxicity of molecules from their molecular structure using the T3DB database.
Building Model to for analysis sentiment on social media ,marketplace, customer review etc.
Add a description, image, and links to the toxicity-classification topic page so that developers can more easily learn about it.
To associate your repository with the toxicity-classification topic, visit your repo's landing page and select "manage topics."