Instructions to use Arm/deit-tiny-int8-litert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use Arm/deit-tiny-int8-litert 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
Sync model repo (text/metadata)
Browse files
README.md
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## Additional notes
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Patch embeddings are kept in FP32 on this export. The model's quantization spec excludes this layer to avoid a static-transpose graph pattern that the XNNPACK delegate cannot compile on the ExecuTorch export; that same declarative skip list is shared across backends, so it also applies to this LiteRT export even though LiteRT itself has no such compile constraint. Latency and memory were measured with the model pinned to a single CPU core on the vivo X300.
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- Sample input: `sample_input.jpg` is derived from [Samoyed on Beach](https://commons.wikimedia.org/wiki/File:Samoyed_on_Beach.jpg) by Appleinfl, via Wikimedia Commons (public domain).
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## About this version
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## Additional notes
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Patch embeddings are kept in FP32 on this export. The model's quantization spec excludes this layer to avoid a static-transpose graph pattern that the XNNPACK delegate cannot compile on the ExecuTorch export; that same declarative skip list is shared across backends, so it also applies to this LiteRT export even though LiteRT itself has no such compile constraint. Latency and memory were measured with the model pinned to a single CPU core on the vivo X300.
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- Sample input: `sample_input.jpg` is derived from [Samoyed on Beach](https://commons.wikimedia.org/wiki/File:Samoyed_on_Beach.jpg) by Appleinfl, via Wikimedia Commons (public domain).
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## About this version
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