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Metaclip B16 400m
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Metaclip B16 400m

Developed by facebook
MetaCLIP is a vision-language model trained on CommonCrawl data for constructing shared image-text embedding spaces
Text-to-Image
Transformers
#Zero-shot image classification#Cross-modal retrieval#CLIP data optimization
Downloads 51
Release Time : 10/9/2023

Model Overview

This model applies the MetaCLIP framework to 400 million data points from CommonCrawl to reveal CLIP training data selection methods, supporting cross-modal understanding between images and text

Model Features

Public data training
Trained on the open CommonCrawl dataset with high data transparency
Cross-modal understanding
Can process both visual and textual information to establish shared embedding spaces
Zero-shot learning
Capable of performing new tasks without task-specific training

Model Capabilities

Zero-shot image classification
Text-based image retrieval
Image-based text retrieval
Cross-modal feature extraction

Use Cases

Content retrieval
Image search engine
Retrieve relevant images using natural language descriptions
Intelligent labeling
Automatic image tagging
Generate descriptive labels for unlabeled images
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