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Openvision Vit Small Patch8 384
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Openvision Vit Small Patch8 384

Developed by UCSC-VLAA
OpenVision is a fully open, cost-effective family of advanced vision encoders focused on multimodal learning.
Multimodal FusionOpen Source License:Apache-2.0#Multimodal Learning#Open Vision Encoder#Cost-Effective
Downloads 21
Release Time : 5/6/2025

Model Overview

The OpenVision model aims to provide efficient visual feature extraction capabilities, supporting multimodal learning tasks. This model family emphasizes openness and cost-effectiveness, making it suitable for a wide range of visual applications.

Model Features

Full Openness
The model is fully open, allowing free use and modification to foster community collaboration and innovation.
Cost-Effective
Designed with cost-efficiency in mind, it maintains high performance while reducing computational resource requirements.
Multimodal Support
Optimized for multimodal learning tasks, it effectively handles various data modalities such as vision and language.

Model Capabilities

Image Feature Extraction
Multimodal Learning
Visual Representation Learning

Use Cases

Computer Vision
Image Retrieval
Efficient similarity-based image search using extracted image features.
Visual Question Answering
Combining text and visual information to answer questions about image content.
Multimodal Applications
Image-Text Matching
Evaluating the relevance between images and textual descriptions.
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