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Vit Base Patch16 Siglip 256.webli
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Vit Base Patch16 Siglip 256.webli

Developed by timm
A ViT-B-16 image encoder model based on SigLIP, using original attention pooling, suitable for image feature extraction tasks.
Image Classification
Transformers
Open Source License:Apache-2.0#SigLIP visual encoding#Original attention pooling#256 resolution processing
Downloads 269
Release Time : 12/24/2024

Model Overview

This model is a ViT-B-16 architecture image encoder based on SigLIP (Sigmoid Loss for Language-Image Pre-training), primarily used for image feature extraction tasks.

Model Features

SigLIP-based pre-training
Utilizes Sigmoid Loss for language-image pre-training, optimizing image feature extraction capabilities.
ViT-B-16 architecture
Employs the Vision Transformer Base 16 architecture, offering robust image processing capabilities.
Original attention pooling
Uses original attention pooling mechanism to enhance the efficiency and accuracy of feature extraction.

Model Capabilities

Image feature extraction
Visual representation learning

Use Cases

Computer vision
Image classification
Can be used for image classification tasks by extracting image features for classifiers.
Image retrieval
Applicable to image retrieval tasks, enabling similar image searches through extracted features.
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