amazon-science/semi-vit
PyTorch implementation of Semi-supervised Vision Transformers
This project offers a powerful method to classify images, even when you have a limited amount of labeled data. It takes your raw image datasets and pre-trained model weights, then outputs a highly accurate image classification model. This is ideal for machine learning engineers and researchers building computer vision systems.
No commits in the last 6 months.
Use this if you need to train a robust image classification model but struggle with the high cost or difficulty of labeling a large dataset.
Not ideal if you do not have significant expertise in machine learning model training or access to substantial computational resources.
Stars
61
Forks
10
Language
Python
License
—
Category
Last pushed
Dec 23, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/amazon-science/semi-vit"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Jittor/jittor
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
zhanghang1989/ResNeSt
ResNeSt: Split-Attention Networks
berniwal/swin-transformer-pytorch
Implementation of the Swin Transformer in PyTorch.
NVlabs/FasterViT
[ICLR 2024] Official PyTorch implementation of FasterViT: Fast Vision Transformers with...
ViTAE-Transformer/ViTPose
The official repo for [NeurIPS'22] "ViTPose: Simple Vision Transformer Baselines for Human Pose...