LitertEmbeddingModel class
- Inheritance
-
- Object
- EmbeddingModel
- LitertEmbeddingModel
Properties
- hashCode → int
-
The hash code for this object.
no setterinherited
- inputSequenceLength → int
-
Sequence length the model was compiled for (input tensor dim
1).no setter - onClose → VoidCallback
-
final
- outputDimension → int
-
Output embedding dimension (output tensor dim
1— 768 for Gecko / EmbeddingGemma).no setter - runtimeType → Type
-
A representation of the runtime type of the object.
no setterinherited
Methods
-
close(
) → Future< void> -
Close the embedding model and release resources.
override
-
generateEmbedding(
String text, {TaskType taskType = TaskType.retrievalQuery}) → Future< List< double> > -
Generate embedding vector for given text.
override
-
generateEmbeddings(
List< String> texts, {TaskType taskType = TaskType.retrievalQuery}) → Future<List< List< >double> > -
Generate embedding vectors for multiple texts.
override
-
getDimension(
) → Future< int> -
Get the dimension of embedding vectors generated by this model.
override
-
noSuchMethod(
Invocation invocation) → dynamic -
Invoked when a nonexistent method or property is accessed.
inherited
-
toString(
) → String -
A string representation of this object.
inherited
Operators
-
operator ==(
Object other) → bool -
The equality operator.
inherited
Static Methods
-
create(
{required String modelPath, required String tokenizerPath, PreferredBackend? preferredBackend, int? inputSequenceLength, int? outputDimension, VoidCallback? onClose}) → Future< LitertEmbeddingModel> -
Load a
.tfliteembedding model from disk and prepare it for inference on a background isolate.