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Aimv2 3b Patch14 224.apple Pt
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Aimv2 3b Patch14 224.apple Pt

Developed by timm
AIM-v2 is an efficient image encoder model compatible with the timm framework, suitable for computer vision tasks.
Image Classification
Transformers
#Large-scale Visual Encoding#Multimodal Pre-training#Apple Ecosystem Optimization
Downloads 50
Release Time : 12/31/2024

Model Overview

This model is an image encoder based on the AIM-v2 architecture, primarily designed for image feature extraction tasks. Its weight files are released by Apple Inc. and are compatible with the timm library, allowing easy integration into existing computer vision workflows.

Model Features

Efficient Image Encoding
Utilizes the AIM-v2 architecture to provide efficient image feature extraction capabilities
timm Compatibility
Fully compatible with the timm framework for easy integration into existing computer vision workflows
Large-scale Pre-training
Trained on 3B parameters, offering robust feature representation capabilities

Model Capabilities

Image Feature Extraction
Computer Vision Task Processing

Use Cases

Computer Vision
Image Classification
Can serve as a feature extractor for image classification tasks
Object Detection
Can be used in the feature extraction phase of object detection tasks
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