WhiteLightning's privacy protection program consists of three layers of safeguards:
- Zero Real Data Requirements: training is entirely dependent on synthetic data generated by LLM, without the need for the user to provide any business data
- end-to-end encryption: API keys are only used for data generation during the training phase (via services such as OpenRouter), the model itself does not contain the raw data
- Runs completely offline: After training, the model can be used in an environment disconnected from the network, avoiding the risk of data transfer in the cloud
For sensitive domains such as healthcare/finance, it is recommended to 1) use privately deployed LLMs to generate data 2) train the model in an isolated network 3) train the model through a --generate-edge-cases Parameter-enhanced models' ability to handle specialized terminology.
This answer comes from the articleWhiteLightning: an open source tool for generating lightweight offline text classification models in one clickThe
May not be reproduced without permission:AI productivity tools " How to train high-quality text classification models without exposing business data?
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