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Rubertconv Toxic Editor
A text purification labeling model based on rubert-base-cased-conversational, supporting four processing types: retain, replace, delete, and insert labels.
Downloads 79
Release Time : 3/2/2022
Model Overview
This model is used for text purification processing, capable of identifying and handling toxic or inappropriate content, supporting four different processing methods, and requires the use of a mask filler.
Model Features
Four Processing Types
Supports retain, replace, delete, and insert processing methods to flexibly meet different purification needs.
Mask Filler Support
Requires the use of a mask filler to intelligently replace toxic content.
Russian Optimization
Based on the Russian dialogue-optimized rubert model, it is particularly suitable for Russian text processing.
Model Capabilities
Text Toxicity Labeling
Text Purification Processing
Russian Text Analysis
Use Cases
Content Moderation
Social Media Comment Purification
Automatically identifies and processes inappropriate comments on social media
Text Preprocessing
Dialogue System Input Purification
Purifies user input before processing by dialogue systems
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