Pavit
P
Pavit
Developed by Ajibola
PaViT is an image recognition model based on Pathway Vision Transformer, inspired by Google's PaLM, focusing on the application of few-shot learning techniques in image recognition tasks.
Image Classification Supports Multiple LanguagesOpen Source License:MIT#Few-shot Learning#CPU Efficient Training#Self-attention Optimization
Downloads 20
Release Time : 2/23/2023
Model Overview
PaViT is a Vision Transformer model for image recognition, designed to demonstrate efficient learning capabilities on small datasets.
Model Features
Few-shot Learning Capability
The model performs excellently on small-scale datasets, achieving high accuracy with only 15,000 images.
CPU Efficient Training
The model is designed for efficient training on CPUs with 4GB memory.
Scalable Architecture
Performance can be further improved by increasing self-attention heads and linear layers.
Model Capabilities
Image Classification
Multi-class Recognition
Use Cases
Animal Recognition
Pet Classification
Identify categories of pets such as cats and dogs
Performs well on a 3-class animal dataset
Wildlife Identification
Identify different species of wild animals
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