Instructions to use litert-community/efficientnet_b6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/efficientnet_b6 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
Updated README.md File
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README.md
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acc@5 (on ImageNet-1K): 96.916%
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num_params: 43,040,704
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## How to Use
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**1. Install Dependencies** Ensure your Python environment is set up with the required libraries. Run the following command in your terminal:
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acc@5 (on ImageNet-1K): 96.916%
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num_params: 43,040,704
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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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## How to Use
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**1. Install Dependencies** Ensure your Python environment is set up with the required libraries. Run the following command in your terminal:
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