litert-community / efficientnet_b1

huggingface.co
Total runs: 334
24-hour runs: 18
7-day runs: 143
30-day runs: 136
Model's Last Updated: September 05 2026
image-classification

Introduction of efficientnet_b1

Model Details of efficientnet_b1

EfficientNet B1

EfficientNet B1 model pre-trained on ImageNet-1k.

Intended uses & limitations

The model files were converted from pretrained weights from PyTorch Vision. The models may have their own licenses or terms and conditions derived from PyTorch Vision and the dataset used for training. It is your responsibility to determine whether you have permission to use the models for your use case.

BibTeX entry and citation info
@article{Tan2019EfficientNetRM,
  title={EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks},
  author={Mingxing Tan and Quoc V. Le},
  journal={ArXiv},
  year={2019},
  volume={abs/1905.11946}
}

Runs of litert-community efficientnet_b1 on huggingface.co

334
Total runs
18
24-hour runs
76
3-day runs
143
7-day runs
136
30-day runs

More Information About efficientnet_b1 huggingface.co Model

efficientnet_b1 huggingface.co

efficientnet_b1 huggingface.co is an AI model on huggingface.co that provides efficientnet_b1's model effect (), which can be used instantly with this litert-community efficientnet_b1 model. huggingface.co supports a free trial of the efficientnet_b1 model, and also provides paid use of the efficientnet_b1. Support call efficientnet_b1 model through api, including Node.js, Python, http.

litert-community efficientnet_b1 online free

efficientnet_b1 huggingface.co is an online trial and call api platform, which integrates efficientnet_b1's modeling effects, including api services, and provides a free online trial of efficientnet_b1, you can try efficientnet_b1 online for free by clicking the link below.

litert-community efficientnet_b1 online free url in huggingface.co:

https://huggingface.co/litert-community/efficientnet_b1

efficientnet_b1 install

efficientnet_b1 is an open source model from GitHub that offers a free installation service, and any user can find efficientnet_b1 on GitHub to install. At the same time, huggingface.co provides the effect of efficientnet_b1 install, users can directly use efficientnet_b1 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

efficientnet_b1 install url in huggingface.co:

https://huggingface.co/litert-community/efficientnet_b1

Url of efficientnet_b1

Provider of efficientnet_b1 huggingface.co

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