litert-community / efficientnet_b2

huggingface.co
Total runs: 159
24-hour runs: 0
7-day runs: 22
30-day runs: 87
Model's Last Updated: September 05 2026
image-classification

Introduction of efficientnet_b2

Model Details of efficientnet_b2

EfficientNet B2

EfficientNet B2 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_b2 on huggingface.co

159
Total runs
0
24-hour runs
1
3-day runs
22
7-day runs
87
30-day runs

More Information About efficientnet_b2 huggingface.co Model

efficientnet_b2 huggingface.co

efficientnet_b2 huggingface.co is an AI model on huggingface.co that provides efficientnet_b2's model effect (), which can be used instantly with this litert-community efficientnet_b2 model. huggingface.co supports a free trial of the efficientnet_b2 model, and also provides paid use of the efficientnet_b2. Support call efficientnet_b2 model through api, including Node.js, Python, http.

litert-community efficientnet_b2 online free

efficientnet_b2 huggingface.co is an online trial and call api platform, which integrates efficientnet_b2's modeling effects, including api services, and provides a free online trial of efficientnet_b2, you can try efficientnet_b2 online for free by clicking the link below.

litert-community efficientnet_b2 online free url in huggingface.co:

https://huggingface.co/litert-community/efficientnet_b2

efficientnet_b2 install

efficientnet_b2 is an open source model from GitHub that offers a free installation service, and any user can find efficientnet_b2 on GitHub to install. At the same time, huggingface.co provides the effect of efficientnet_b2 install, users can directly use efficientnet_b2 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

efficientnet_b2 install url in huggingface.co:

https://huggingface.co/litert-community/efficientnet_b2

Url of efficientnet_b2

Provider of efficientnet_b2 huggingface.co

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