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Nli Deberta Base

Developed by cross-encoder
Natural language inference cross-encoder based on DeBERTa architecture, used to determine logical relationships between sentence pairs
Downloads 2,299
Release Time : 3/2/2022

Model Overview

This model is trained using the SentenceTransformers framework, specifically designed for natural language inference tasks, capable of determining the logical relationship (contradiction, entailment, or neutral) between two sentences.

Model Features

Natural Language Inference
Accurately determines the logical relationship (contradiction, entailment, or neutral) between two sentences
Zero-shot Classification
Supports zero-shot classification tasks, enabling classification without domain-specific training data
Multilingual Support
While primarily targeting Chinese, the DeBERTa-based architecture also enables processing of other languages

Model Capabilities

Natural Language Inference
Zero-shot Classification
Text Relation Analysis

Use Cases

Text Analysis
Contradiction Detection
Detects whether there is a contradictory relationship between two sentences
Accurately identifies contradictory statements in text
Logical Reasoning
Determines whether one sentence entails the meaning of another
Can be used to build reasoning modules for question-answering systems
Content Moderation
Fact Checking
Verifies whether new content aligns with known facts
Helps identify false or contradictory information
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