@brief Sets whether L2 normalization should be performed on the returned embeddings.
Use this option only if the model does not already contain a native L2_NORMALIZATION TF Lite Op.
In most cases, this is already the case and L2 norm is thus achieved through TF Lite inference.
@brief Sets whether the returned embedding should be quantized to bytes via scalar quantization.
Embeddings are implicitly assumed to be unit-norm and therefore any dimensions is guaranteed to
have value in [-1.0, 1.0]. Use thel2Normalizeproperty if this is not the case.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2026-05-28 UTC."],[],[]]
