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Openvision Vit Base Patch8 160

Developed by UCSC-VLAA
OpenVision-ViT-Tiny is a fully open, cost-effective advanced visual encoder, part of the OpenVision family, focusing on multimodal learning.
Downloads 26
Release Time : 5/6/2025

Model Overview

This model is a lightweight Vision Transformer designed for efficient image feature extraction, suitable for multimodal learning tasks.

Model Features

Fully Open
The model is completely open, facilitating research and commercial use.
Cost-Effective
Designed with computational efficiency in mind, reducing resource requirements while maintaining performance.
Lightweight
The Tiny version is particularly suitable for resource-constrained environments.

Model Capabilities

Image Feature Extraction
Multimodal Learning Support

Use Cases

Computer Vision
Image Classification
Can be used as a feature extractor for image classification tasks
Multimodal Learning
Used for vision-language joint representation learning
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