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Vit Test 1 95
V
Vit Test 1 95
Developed by 25khattab
This is an image classification model based on the Vision Transformer architecture, achieving an accuracy of 95.02%.
Downloads 15
Release Time : 6/10/2022
Model Overview
This model is designed for image classification tasks, automatically generated via the HuggingPics framework, and suitable for various image recognition scenarios.
Model Features
High Accuracy
Achieves 95.02% accuracy on the test set, demonstrating excellent performance.
Based on ViT Architecture
Utilizes the Vision Transformer architecture, effectively capturing global features in images.
Ease of Use
Automatically generated via the HuggingPics framework, facilitating quick deployment and usage.
Model Capabilities
Image Classification
Object Recognition
Use Cases
General Image Recognition
Everyday Object Classification
Classifies and recognizes everyday objects
Accuracy reaches 95.02%
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