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Deberta V3 Large Mnli Fever Anli Ling Wanli Binary
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Deberta V3 Large Mnli Fever Anli Ling Wanli Binary

Developed by MoritzLaurer
This model is a zero-shot classification model based on the DeBERTa-v3-large architecture, primarily trained on five NLI datasets, suitable for tasks that strictly follow the original NLI task format.
Text Classification
Transformers
 EnglishOpen Source License:MIT#NLI task specific#Zero-shot classification benchmark#Multi-dataset training
Downloads 30
Release Time : 11/27/2023

Model Overview

This model is mainly used for text classification tasks, especially in zero-shot classification scenarios. It was created as a comparative benchmark for another more comprehensive model, suitable for tasks that strictly adhere to the original NLI task format.

Model Features

NLI dataset training
The model was trained on five NLI datasets, focusing on natural language inference tasks.
Zero-shot classification capability
Supports zero-shot classification tasks without requiring task-specific fine-tuning.
Comparative benchmark
Primarily created as a comparative benchmark for more comprehensive models.

Model Capabilities

Text classification
Zero-shot inference
Natural language inference

Use Cases

Text analysis
Zero-shot text classification
Classify unseen text categories without requiring specific training data.
Natural language inference
Determine the logical relationship between two sentences (entailment, contradiction, or neutral).
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