metadata
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
metrics:
- accuracy
Model card for hpx_former_s18
The model hpx_former_s18 is part of the HyenaPixel model family proposed in the paper "HyenaPixel: Global Image Context with Convolutions". HyenaPixel uses large convolutions as an attention replacement by extending Hyena (Paper and GitHub) to support bidirectrional and two-dimensional input. The operator is integrated in the MetaFormer (Paper and GitHub) framework.
The official PyTorch implementation of HyenaPixel can be found on GitHub.
Models
Model | Resolution | Params | Top1 Acc | Download |
---|---|---|---|---|
hpx_former_s18 | 224 | 29M | 83.2 | HuggingFace |
hpx_former_s18_384 | 384 | 29M | 84.7 | HuggingFace |
hb_former_s18 | 224 | 28M | 83.5 | HuggingFace |
c_hpx_former_s18 | 224 | 28M | 83.0 | HuggingFace |
hpx_a_former_s18 | 224 | 28M | 83.6 | HuggingFace |
hb_a_former_s18 | 224 | 27M | 83.2 | HuggingFace |
hpx_former_b36 | 224 | 111M | 84.9 | HuggingFace |
hb_former_b36 | 224 | 102M | 85.2 | HuggingFace |
Usage
pip install git+https://github.com/spravil/HyenaPixel.git
import timm
import hyenapixel.models
model = timm.create_model("hpx_former_s18", pretrained=True)
Bibtex
@article{spravil2024hyenapixel,
title={HyenaPixel: Global Image Context with Convolutions},
author={Julian Spravil and Sebastian Houben and Sven Behnke},
journal={arXiv preprint arXiv:2402.19305},
year={2024},
}