nlp api analytics text-classification transformers onnx toxic-comments fastapi onnxruntime toxicity-classification llm ... It is a trained Deep Learning model to predict different level of toxic comments.

This repository contains code to instantiate and deploy a toxic comment classifier. This model is able to detect 6 types of toxicity in a text fragment.

This model is trained for toxicity classification task. The dataset used for training is the merge of the English parts of the three datasets by Jigsaw (Jigsaw 2018, Jigsaw 2019, Jigsaw 2020), containing around 2 million examples. We split it into two parts and fine-tune a RoBERTa model (RoBERTa: A Robustly Optimized BERT Pretraining Approach) on it.

This is an instance of xlm-roberta-large that was fine-tuned on binary toxicity classification task based on our compiled dataset textdetox/multilingual_toxicity_dataset.

June 27, 2023 - This has been done with a body of newly developed adversarial attacks designed to fool machine translation, question answering, and text classification systems. In this post, we train a transformer-based toxicity language classifier using Hugging Face, test the trained model on adversarial ...

Repository for all things related to classifying whether a text is toxic or not using data from https://github.com/TurkuNLP/wikipedia-toxicity-data-fi - TurkuNLP/toxicity-classifier

any piece of text and detecting different types of toxicity like obscenity,

December 15, 2021 - The toxicity model detects whether text contains toxic content such as threatening language, insults, obscenities, identity-based hate, or sexually explicit language. The toxicity classifier model was trained on the civil comments dataset ...

BERT base model (uncased) fine tuned on Jigsaw Unintended Bias in Toxicity Classification

Toxicity classifier trained on civil comments dataset.

November 13, 2024 - Make sure to use a model that's compatible with classification tasks. TensorFlow.js toxicity classifier.

A simple toxicity classifier using TensorFlow.js and Next.js

Natural Language Processing. Toxicity detection is a task within this area that aims to identify toxic · language online, and classification models are used for this purpose.

The Toxicity Classification Model is a powerful tool that helps identify toxic language in text.

A comprehensive machine learning project for detecting and classifying toxic comments across multiple toxicity categories and severity levels. Starting with a traditional ML-based classifier, this project was extended to explore advanced AI-powered ...

Machine Learning eXchange (MLX). Data and AI Assets Catalog and Execution Engine - claimed-framework/mlx

May 1, 2021 - Explore and run AI code with Kaggle Notebooks | Using data from Toxic Comment Classification Challenge

This is an instance of xlm-roberta-large that was fine-tuned on binary toxicity classification task based on our updated (2025) dataset textdetox/multilingual_toxicity_dataset.

February 15, 2022 - Checking your browser before accessing ncbi.nlm.nih.gov · Click here if you are not automatically redirected after 5 seconds

Trained models & code to predict toxic comments on 3 Jigsaw challenges: Toxic comment classification, Unintended Bias in Toxic comments, Multilingual toxic comment classification.