README.md

---
license: apache-2.0
datasets:
- ILSVRC/imagenet-1k
pipeline_tag: image-classification
---
# Introduction

This repository stores the model for Efficientnet-b4, compatible with Kalray's neural network API. </br>
Please see www.github.com/kalray/kann-models-zoo for details and proper usage. </br>
Please see https://huggingface.co/docs/transformers/main/en/model_doc/efficientnet for Efficientnet model description. </br>

# Contents

- ONNX: efficientNet-b4.onnx
- Quantized ONNX (INT8): efficientNet-b4-q.onnx

# Lecture note reference

- EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks, https://arxiv.org/pdf/1905.11946

# Repository or links references

- [PyTorch | TorchVision](https://pytorch.org/vision/stable/models/generated/torchvision.models.efficientnet_b4.html#torchvision.models.efficientnet_b4)

BibTeX entry and citation info
```
@inproceedings{he2016deep,
  title     = {Deep residual learning for image recognition},
  author    = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle = {Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages     = {770--778},
  year      = {2016}
}
```

Authors:
+ [email protected]
+ [email protected]