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zeekay
bde2e2531b
Machine Learning with FHE - fork of Zama Concrete-ML - Built-in FHE-friendly ML models - scikit-learn compatible API - PyTorch model conversion - Quantization-aware training
21 lines
368 B
Makefile
21 lines
368 B
Makefile
# Useful for jupyter notebooks
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export LC_ALL=en_US.UTF-8
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export LANG=en_US.UTF-8
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TIME_NB="${USE_CASE_DIR}/time_notebook_execution.sh"
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run_example: four
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one:
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@$(TIME_NB) FromImageNetToCifar.ipynb
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two: one
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@$(TIME_NB) CifarQuantizationAwareTraining.ipynb
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three: two
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@$(TIME_NB) CifarInFhe.ipynb
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four: three
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@$(TIME_NB) CifarInFheWithSmallerAccumulators.ipynb
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