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Developed by Raffix
A zero-shot classification model based on the Transformers library, supporting English text classification tasks.
Downloads 21
Release Time : 2/20/2024

Model Overview

This model utilizes a pre-trained Transformer architecture for zero-shot classification, enabling text classification without task-specific training data.

Model Features

Zero-shot learning
Classify without task-specific training data
Multi-category support
Capable of handling various classification tasks
Pre-trained models
Based on large-scale pre-trained Transformer architecture

Model Capabilities

Text classification
Zero-shot learning
Multi-label classification

Use Cases

Text analysis
Sentiment analysis
Analyze text sentiment without training
Can identify positive, negative, or neutral sentiment
Topic classification
Classify news or articles by topic
Can identify topics like sports, technology, politics
Content moderation
Harmful content detection
Identify inappropriate content in text
Can flag hate speech, violent content, etc.
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