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CLIP ViT B 32 CommonPool.S.laion S13m B4k
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CLIP ViT B 32 CommonPool.S.laion 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 58
Release Time : 4/26/2023

Model Overview

This model is a variant of the CLIP architecture, combining the ViT-B-32 visual encoder and text encoder. It is trained on image-text pairs through contrastive learning, enabling zero-shot image classification and cross-modal retrieval.

Model Features

Zero-shot learning capability
Can be directly applied to new image classification tasks without task-specific fine-tuning
Cross-modal understanding
Capable of understanding both visual and textual information for image-text matching
Efficient architecture
Based on the ViT-B-32 visual encoder, balancing performance and computational efficiency

Model Capabilities

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

Use Cases

Content retrieval
Image search engine
Retrieve relevant images using natural language queries
Enables flexible search without predefined labels
Automatic labeling
Automatic image labeling
Generate descriptive labels for unlabeled images
Reduces manual labeling workload
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