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Vit Large Patch14 Clip 224.metaclip 2pt5b
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Vit Large Patch14 Clip 224.metaclip 2pt5b

Developed by timm
A dual-framework compatible vision model trained on MetaCLIP-2.5B dataset, supporting zero-shot image classification tasks
Image Classification
Safetensors
#Zero-shot image classification#Multi-framework compatibility#Large-scale pre-training
Downloads 2,648
Release Time : 10/23/2024

Model Overview

This model is a large-scale vision model based on Vision Transformer architecture, compatible with both open_clip and timm frameworks, primarily used for zero-shot image classification tasks.

Model Features

Dual-framework compatibility
Compatible with both open_clip and timm frameworks, providing more flexible usage options
Large-scale pre-training
Trained on the large-scale MetaCLIP-2.5B dataset, featuring powerful feature extraction capabilities
Zero-shot learning
Supports zero-shot image classification tasks without requiring specific category training

Model Capabilities

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

Use Cases

Image classification
Open-domain image classification
Classify images of arbitrary categories without specific training
Content understanding
Image content analysis
Extract high-level semantic features from images
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