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Vit Base Patch16 Clip 224.laion2b
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Vit Base Patch16 Clip 224.laion2b

Developed by timm
Vision Transformer model based on CLIP architecture, containing only the image encoder part, suitable for image feature extraction tasks
Image Classification
Transformers
Open Source License:Apache-2.0#Multimodal Image Encoding#Zero-shot Visual Classification#Large-scale Pretraining
Downloads 4,460
Release Time : 12/24/2024

Model Overview

This model is the visual encoder component of the CLIP framework, using ViT-B/16 architecture, trained on the laion2B dataset, capable of extracting high-quality image feature representations

Model Features

Large-scale Pretraining
Trained on the massive laion2B dataset containing 3.4 billion samples
Efficient Image Encoding
Based on Vision Transformer architecture, efficiently processes 224x224 resolution images
Multimodal Compatibility
Although only containing the image encoder, its feature space aligns with CLIP's text encoder

Model Capabilities

Image feature extraction
Image similarity computation
Visual content understanding

Use Cases

Computer Vision
Image Retrieval
Similar image search through extracted image features
Visual Content Analysis
Extract high-level semantic features from images for classification or tagging
Multimodal Applications
Image-Text Matching
Collaborate with CLIP's text encoder to achieve cross-modal retrieval
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