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Siglip2 Large Patch16 256

Developed by google
SigLIP 2 is an improved vision-language model based on SigLIP, integrating multiple technologies to enhance semantic understanding, localization, and dense feature extraction capabilities.
Downloads 10.89k
Release Time : 2/17/2025

Model Overview

This model can be used for tasks such as zero-shot image classification and image-text retrieval, or as a visual encoder for vision-language models.

Model Features

Enhanced Semantic Understanding
Integrates multiple technologies to improve semantic understanding.
Improved Localization Capability
Enhanced localization capability through additional training objectives.
Dense Feature Extraction
Capable of extracting high-quality dense image features.
Unified Training Scheme
Adopts a unified training scheme that integrates multiple independently developed technologies.

Model Capabilities

Zero-shot Image Classification
Image-Text Retrieval
Image Feature Extraction

Use Cases

Image Classification
Zero-shot Image Classification
Classify images without fine-tuning.
Image-Text Retrieval
Image Search
Retrieve relevant images based on text descriptions.
Visual Encoding
Visual Feature Extraction
Serves as a visual encoder to provide image features for other vision tasks.
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