Hiera-small-224-hf Open-source Visual Model - Small Number of Parameters, Efficiently Completes Image Classification Tasks

Hiera Small 224 Hf

Developed by onnx-community

Hiera is an efficient vision Transformer model designed for image classification tasks, featuring a small parameter count and high computational performance.

Image Classification

Transformers

#Web adaptation #ONNX format #Lightweight vision

Downloads 16

Release Time : 8/29/2024

Model Overview

Hiera Small 224 is a vision model based on the Transformer architecture, suitable for computer vision tasks such as image classification. It achieves efficient inference speed through optimized architectural design.

Model Features

Efficient architecture

Uses an optimized Transformer architecture to reduce computational resource requirements while maintaining performance.

Compact model size

Designed for resource-constrained environments, suitable for deployment on edge devices.

ONNX support

Provides ONNX format weights for easy deployment on various platforms.

Model Capabilities

Image classification

Visual feature extraction

Use Cases

Computer vision

Image classification

Classify and recognize input images

Edge device vision applications

Deploy visual recognition functions on resource-constrained devices

Property	Details
Base Model	facebook/hiera-small-224-hf
Library Name	transformers.js

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Hiera Small 224 Hf

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Facebook Hiera Small 224 HF with Transformers.js

🚀 Quick Start

📚 Documentation