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Vit Large Patch14 Clip 224.metaclip 400m
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Vit Large Patch14 Clip 224.metaclip 400m

Developed by timm
Vision Transformer model trained on MetaCLIP-400M dataset, supporting zero-shot image classification tasks
Image Classification
Safetensors
#Zero-shot image classification#Multi-framework compatibility#Large-scale pre-training
Downloads 294
Release Time : 10/23/2024

Model Overview

This is a dual-purpose Vision Transformer model compatible with both open_clip and timm frameworks, primarily used for zero-shot image classification tasks

Model Features

Dual-framework compatibility
Supports both open_clip and timm frameworks, offering more flexible usage
Zero-shot learning capability
Capable of classification without category-specific training, with strong generalization ability
Large-scale pre-training
Trained on MetaCLIP-400M dataset with rich visual concept understanding

Model Capabilities

Zero-shot image classification
Visual feature extraction
Cross-modal understanding

Use Cases

Image understanding
Open-domain image classification
Classify images of arbitrary categories without specific training
Visual content analysis
Extract high-level semantic features from images
Multimodal applications
Image-text matching
Evaluate the matching degree between images and text descriptions
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