public static abstract class
TextEmbedder.TextEmbedderOptions.Builder
Builder for TextEmbedder.TextEmbedderOptions.
Public Constructors
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Builder()
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Public Methods
| abstract TextEmbedder.TextEmbedderOptions |
build()
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| abstract TextEmbedder.TextEmbedderOptions.Builder | |
| abstract TextEmbedder.TextEmbedderOptions.Builder |
setL2Normalize(boolean l2Normalize)
Sets whether L2 normalization should be performed on the returned embeddings.
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| abstract TextEmbedder.TextEmbedderOptions.Builder |
setQuantize(boolean quantize)
Sets whether the returned embedding should be quantized to bytes via scalar quantization.
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Inherited Methods
Public Constructors
public Builder ()
Public Methods
public abstract TextEmbedder.TextEmbedderOptions.Builder setBaseOptions (BaseOptions value)
Sets the base options for the text embedder task.
Parameters
| value |
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public abstract TextEmbedder.TextEmbedderOptions.Builder setL2Normalize (boolean l2Normalize)
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.
False by default.
Parameters
| l2Normalize |
|---|
public abstract TextEmbedder.TextEmbedderOptions.Builder setQuantize (boolean quantize)
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 setL2Normalize(boolean)
if this is not the case.
False by default.
Parameters
| quantize |
|---|