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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
10 lines
420 B
Bash
Executable File
10 lines
420 B
Bash
Executable File
#! /bin/env bash
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bash download_data.sh && \
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docker build --tag train_sentiment_analysis --file Dockerfile.train . && \
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docker run --name train_sentiment_analysis_container train_sentiment_analysis && \
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docker cp train_sentiment_analysis_container:/project/dev . &&
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docker cp train_sentiment_analysis_container:/project/hf_cache .
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docker rm "$(docker ps -a --filter name=train_sentiment_analysis_container -q)"
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