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CLIP ViT B 32 CommonPool.M.text S128m B4k
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CLIP ViT B 32 CommonPool.M.text 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#General Visual Representation
Downloads 68
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 correlation between images and text, suitable for cross-modal retrieval and classification tasks.

Model Features

Zero-shot Learning Capability
Can perform new image classification tasks without task-specific fine-tuning
Cross-modal Understanding
Capable of processing and understanding both visual and textual information
Efficient Architecture
Vision encoder based on ViT-B/32, balancing performance and computational efficiency

Model Capabilities

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

Use Cases

Content Retrieval
Text-based Image Search
Search for relevant images using natural language descriptions
Automatic Tagging
Image Auto-tagging
Generate descriptive labels for images
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