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--- |
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license: apache-2.0 |
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datasets: |
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- ILSVRC/imagenet-1k |
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pipeline_tag: image-classification |
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--- |
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# Introduction |
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This repository stores the model for Efficientnet-b4, compatible with Kalray's neural network API. </br> |
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Please see www.github.com/kalray/kann-models-zoo for details and proper usage. </br> |
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Please see https://huggingface.co/docs/transformers/main/en/model_doc/efficientnet for Efficientnet model description. </br> |
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# Contents |
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- ONNX: efficientNet-b4.onnx |
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- Quantized ONNX (INT8): efficientNet-b4-q.onnx |
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# Lecture note reference |
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- EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks, https://arxiv.org/pdf/1905.11946 |
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# Repository or links references |
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- [PyTorch | TorchVision](https://pytorch.org/vision/stable/models/generated/torchvision.models.efficientnet_b4.html#torchvision.models.efficientnet_b4) |
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BibTeX entry and citation info |
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``` |
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@inproceedings{he2016deep, |
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title = {Deep residual learning for image recognition}, |
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author = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian}, |
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booktitle = {Proceedings of the IEEE conference on computer vision and pattern recognition}, |
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pages = {770--778}, |
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year = {2016} |
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} |
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``` |
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Authors: |
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+ qmuller@kalrayinc.com |
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+ nbouberbachene@kalrayinc.com |
