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Vit So400m Patch14 Siglip Gap 384.webli
基於SigLIP的視覺Transformer模型，採用全局平均池化處理圖像特徵
Downloads 96
Release Time : 12/24/2024
Model Overview
該模型是一個視覺Transformer架構的圖像編碼器，基於SigLIP方法訓練，主要用於圖像特徵提取任務。模型採用384x384分辨率輸入和14x14的patch大小，通過全局平均池化(GAP)輸出特徵。
Model Features
SigLIP訓練方法
採用SigLIP(Sigmoid Loss for Language-Image Pre-training)方法訓練，優化圖像-文本對齊能力
全局平均池化
在模型末端使用全局平均池化層(GAP)提取圖像特徵，簡化特徵表示
高分辨率處理
支持384x384像素的輸入分辨率，適合處理高質量圖像
Model Capabilities
圖像特徵提取
視覺表示學習
Use Cases
計算機視覺
圖像檢索
提取圖像特徵用於相似圖像搜索
視覺內容分析
分析圖像內容並生成緊湊的特徵表示
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