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Distilbert Topic Abstract Classification

Developed by Eitanli
A text classification model fine-tuned based on distilbert-base-uncased for topic abstract classification tasks
Downloads 43
Release Time : 10/11/2023

Model Overview

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset, primarily used for text classification tasks, with potential application scenarios including topic classification or abstract classification.

Model Features

Lightweight Model
Based on the DistilBERT architecture, smaller and faster than standard BERT models while maintaining good performance
Efficient Fine-tuning
Fine-tuned for specific tasks, suitable for topic and abstract classification applications

Model Capabilities

Text Classification
Topic Identification
Abstract Classification

Use Cases

Academic Research
Paper Abstract Classification
Classify academic paper abstracts to identify their disciplinary fields
Content Management
News Topic Classification
Classify news articles by topic for content organization and retrieval
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