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Rubert Ner Toxicity
A Russian toxicity text named entity recognition model fine-tuned based on ruBERT-tiny, capable of identifying toxic content in text
Downloads 59
Release Time : 3/2/2022
Model Overview
This model is a named entity recognition model fine-tuned on the toxic_dataset_ner dataset, based on cointegrated/rubert-tiny-toxicity, specifically designed to detect toxic content in Russian text.
Model Features
Toxic Content Identification
Accurately identifies toxic content and offensive language in Russian text
Lightweight Model
Based on ruBERT-tiny architecture, the model is small in size and fast in inference
Named Entity Recognition
Not only detects toxic content but also identifies specific toxic entities and phrases
Model Capabilities
Russian Text Analysis
Toxic Content Detection
Named Entity Recognition
Text Classification
Use Cases
Content Moderation
Social Media Comment Moderation
Automatically detects toxic content in social media comments
Can identify offensive language and hate speech
Online Community Management
Helps administrators quickly discover and handle inappropriate remarks
Improves community content quality
Mental Health Applications
Cyberbullying Detection
Identifies cyberbullying remarks that may cause psychological harm
Early intervention in cyberbullying behavior
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