S

Samvit Base Patch16.sa1b

Developed by timm
Segment-Anything Vision Transformer (SAM ViT) image feature model, which only includes feature extraction and fine-tuning capabilities, without a segmentation head.
Downloads 2,756
Release Time : 5/18/2023

Model Overview

This model is an image feature extraction model based on the Vision Transformer (ViT) architecture, primarily used for image classification and feature extraction tasks. It was pretrained by the paper authors on the SA-1B dataset with MAE weight initialization, making it suitable for segmentation tasks.

Model Features

Efficient Feature Extraction
This model focuses on image feature extraction and is suitable for various downstream vision tasks.
Vision Transformer Architecture
Utilizes the advanced Vision Transformer (ViT) architecture, capable of effectively processing high-resolution images.
Large-Scale Pretraining
Pretrained on the SA-1B dataset, offering strong generalization capabilities.

Model Capabilities

Image Feature Extraction
Image Classification
Image Embedding Generation

Use Cases

Computer Vision
Image Classification
Can be used to classify images and identify the main content within them.
Feature Extraction
Can be used to extract image features for downstream tasks.
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