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Vit So400m Patch16 Siglip 256.v2 Webli
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Vit So400m Patch16 Siglip 256.v2 Webli

Developed by timm
SigLIP 2 ViT model, containing only the image encoder part for image feature extraction, trained on the WebLI dataset.
Text-to-Image
Transformers
Open Source License:Apache-2.0#Multimodal Visual Encoding#Enhanced Semantic Understanding#Dense Feature Extraction
Downloads 12.56k
Release Time : 2/21/2025

Model Overview

This is a Vision Transformer (ViT) model based on the SigLIP 2 architecture, specifically designed for image feature extraction. It employs a Sigmoid loss function for language-image pretraining, offering improved semantic understanding and localization capabilities.

Model Features

SigLIP 2 Architecture
Utilizes the improved SigLIP 2 architecture for better semantic understanding and localization capabilities.
Sigmoid Loss Function
Employs Sigmoid loss for language-image pretraining, enhancing model performance.
Dense Feature Extraction
Capable of extracting dense image features, suitable for various downstream vision tasks.

Model Capabilities

Image Feature Extraction
Semantic Understanding
Image Localization

Use Cases

Computer Vision
Image Retrieval
Uses extracted image features for similar image retrieval.
Visual Question Answering
Serves as the image encoder for visual question answering systems.
Multimodal Applications
Image-Text Matching
Used to evaluate the matching degree between images and text descriptions.
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