Rubert Tiny Bilingual Nli
A Russian natural language inference model fine-tuned from rubert-tiny for predicting logical relationships between texts
Downloads 122
Release Time : 3/2/2022
Model Overview
This model is specifically designed to predict logical relationships (entailment or non-entailment) between two short texts, fine-tuned based on the Russian BERT tiny architecture
Model Features
Russian Optimization
A natural language inference model specifically optimized for Russian texts
Tiny Architecture
Based on the BERT tiny architecture, reducing resource consumption while maintaining performance
Zero-shot Classification
Supports zero-shot classification tasks without requiring domain-specific training data
Model Capabilities
Textual Entailment Recognition
Natural Language Inference
Sentiment Analysis
Zero-shot Classification
Use Cases
Customer Feedback Analysis
Sentiment Polarity Classification
Analyze sentiment tendencies in customer reviews
Can accurately distinguish between satisfied/dissatisfied customer feedback
Content Moderation
Prohibited Content Detection
Identify whether text contains specific types of prohibited content
Featured Recommended AI Models