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Levit 128

Developed by facebook
LeViT-128 is an image classification model based on the Vision Transformer architecture, achieving efficient inference by combining the advantages of convolutional networks.
Downloads 44
Release Time : 6/1/2022

Model Overview

The LeViT-128 model is pretrained on the ImageNet-1k dataset at 224x224 resolution and can classify images into 1,000 categories.

Model Features

Efficient Inference
Achieves faster inference speed than traditional Vision Transformers by leveraging the advantages of convolutional networks.
Hybrid Architecture
Innovatively combines Transformer and convolutional networks, incorporating the strengths of both.

Model Capabilities

Image Classification
Visual Feature Extraction

Use Cases

Computer Vision
Object Recognition
Identify object categories in images
Can accurately classify 1,000 categories from ImageNet
Visual Content Analysis
Analyze image content and extract features
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