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CLIP ViT B 32 CommonPool.S S13m B4k
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CLIP ViT B 32 CommonPool.S 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 Contrastive Learning#Large-scale Pretraining
Downloads 79
Release Time : 4/26/2023

Model Overview

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

Model Features

Zero-shot Learning Capability
Can perform image classification tasks without task-specific fine-tuning
Cross-modal Understanding
Capable of processing and understanding both visual and textual information
Efficient Architecture
Balanced architecture based on Vision Transformer, considering both performance and efficiency

Model Capabilities

Zero-shot Image Classification
Image-Text Matching
Cross-modal Retrieval

Use Cases

Content Moderation
Inappropriate Content Detection
Automatically identify image content that violates community standards
E-commerce
Product Categorization
Automatically categorize product images based on descriptions
Media Analysis
Image Tagging
Generate descriptive tags for images
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