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zeekay
9546c92611
ML examples: - credit_scoring: Credit risk prediction with HMEQ data - disease_prediction: Healthcare ML on encrypted records - cifar: Encrypted image classification - federated_learning: Distributed FHE training - hybrid_model: Mixed FHE/plaintext inference Deployment: - breast_cancer: Cancer detection API - sentiment_analysis: Encrypted NLP - server: FHE inference server Blockchain: - hardhat-template: Solidity + FHE - react-template: Full dApp with FHE
14 lines
457 B
Bash
14 lines
457 B
Bash
#!/bin/bash
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uname_str=$(uname)
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echo "${uname_str}"
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if [[ $uname_str != "Darwin" ]]; then
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echo "Not Darwin"
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# tune the cpu-list according to the resources you want to allocate to it
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taskset --cpu-list 0-12 python serve_model.py --port 8000 --path-to-models ./compiled_models
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# No-limit
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# PATH_TO_MODELS="compiled_models" PORT=8000 python serve_model.py
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else
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echo "Darwin"
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python serve_model.py --port 8000 --path-to-models ./compiled_models
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fi
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