Instructions to use litert-community/efficientnet_b2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/efficientnet_b2 with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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# EfficientNet B2
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EfficientNet B2 model pre-trained on ImageNet-1k.
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# EfficientNet B2
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EfficientNet B2 model pre-trained on ImageNet-1k.
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## Intended uses & limitations
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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.
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### BibTeX entry and citation info
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```bibtex
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@article{Tan2019EfficientNetRM,
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title={EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks},
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author={Mingxing Tan and Quoc V. Le},
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journal={ArXiv},
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year={2019},
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volume={abs/1905.11946}
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}
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```
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