Instructions to use litert-community/MobileNet-v3-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/MobileNet-v3-large 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
Update model card
Browse files
README.md
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`mobilenet_v3_large_int8_channelwise.tflite` was produced with the `STATIC_WI8_AI8` quantization recipe. Weights are signed INT8 and use symmetric channelwise quantization for weight tensors. Activations are signed INT8 with asymmetric quantization parameters.
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The INT8 channelwise artifact keeps standard LiteRT/TFLite model structure before AOT compilation. Local LiteRT compiler checks fully delegated this artifact
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## Intended uses & limitations
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`mobilenet_v3_large_int8_channelwise.tflite` was produced with the `STATIC_WI8_AI8` quantization recipe. Weights are signed INT8 and use symmetric channelwise quantization for weight tensors. Activations are signed INT8 with asymmetric quantization parameters.
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The INT8 channelwise artifact keeps standard LiteRT/TFLite model structure before AOT compilation. Local LiteRT compiler checks fully delegated this artifact on tested compatible NPU backends. Enablement for other NPU backends is still under validation.
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## Intended uses & limitations
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