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Distilroberta Nli
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Distilroberta Nli

Developed by matekadlicsko
This model is a lightweight natural language inference model based on DistilRoBERTa, supporting zero-shot classification tasks.
Text Classification
Transformers
 EnglishOpen Source License:Apache-2.0#Zero-shot reasoning#English NLI#Lightweight RoBERTa
Downloads 18
Release Time : 10/11/2023

Model Overview

This model is specifically designed for Natural Language Inference (NLI) tasks, based on the distilled version of the RoBERTa architecture, and fine-tuned on the multi_nli and English xnli datasets.

Model Features

Lightweight Design
Based on the distilled version of RoBERTa, the model has fewer parameters and faster inference speed.
Zero-shot Classification
Supports zero-shot classification tasks, enabling classification without task-specific training data.
Multi-dataset Fine-tuning
Fine-tuned on multi_nli and English xnli datasets, enhancing the model's generalization capability.

Model Capabilities

Natural Language Inference
Zero-shot Classification
Text Classification

Use Cases

Text Analysis
Sentiment Analysis
Use this model to determine the sentiment tendency of text.
Topic Classification
Classify text content by topic.
Question Answering Systems
Question-Answer Matching
Determine the logical relationship between questions and answers.
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