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CLIP ViT B 32 CommonPool.M.image S128m B4k
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CLIP ViT B 32 CommonPool.M.image S128m 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 73
Release Time : 4/26/2023

Model Overview

This model is a variant of the CLIP architecture, using ViT-B-32 as the visual encoder and trained on the CommonPool.M dataset. It supports cross-modal understanding of images and text, suitable for tasks like 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 understanding both image and text information, establishing connections between them
Efficient Visual Encoding
Uses ViT-B-32 architecture for efficient image feature extraction

Model Capabilities

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

Use Cases

Content Management
Automatic Image Tagging
Automatically generates descriptive tags for unlabeled images
E-commerce
Product Categorization
Automatically categorizes product images based on descriptions
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