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CLIP ViT B 32 CommonPool.S.text S13m B4k
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CLIP ViT B 32 CommonPool.S.text S13m B4k

Developed by laion
A vision-language model based on the CLIP architecture, supporting zero-shot image classification tasks
Text-to-ImageOpen Source License:MIT#Zero-shot image classification#Multimodal understanding#Large-scale pretraining
Downloads 57
Release Time : 4/26/2023

Model Overview

This model is a variant of the CLIP architecture, combining a Vision Transformer (ViT) and a text encoder, capable of understanding the relationship between images and text, suitable for cross-modal tasks such as zero-shot image classification.

Model Features

Zero-shot learning capability
Capable of performing image classification tasks without task-specific fine-tuning
Cross-modal understanding
Able to process and understand both visual and textual information simultaneously
Efficient architecture
Vision encoder based on ViT-B/32 provides a good balance between performance and efficiency

Model Capabilities

Zero-shot image classification
Image-text matching
Cross-modal retrieval

Use Cases

Content moderation
Inappropriate content identification
Automatically identify inappropriate images based on text descriptions
E-commerce
Product categorization
Automatically categorize product images based on product descriptions
Media analysis
Image captioning
Generate relevant text labels for images
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