mp.tasks.text.TextEmbedderOptions

Options for the text embedder task.

mp.tasks.text.TextEmbedderOptions(
    base_options: mp.tasks.BaseOptions,
    l2_normalize: Optional[bool] = None,
    quantize: Optional[bool] = None
)

base_options Base options for the text embedder task.
l2_normalize Whether to normalize the returned feature vector with L2 norm. 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.
quantize Whether the returned embedding should be quantized to bytes via scalar quantization. Embeddings are implicitly assumed to be unit-norm and therefore any dimension is guaranteed to have a value in [-1.0, 1.0]. Use the l2_normalize option if this is not the case.

Methods

to_ctypes

View source

to_ctypes() -> _TextEmbedderOptionsC

Generates a ctypes TextEmbedderOptionsC object.

__eq__

__eq__(
    other
)

l2_normalize None
quantize None