TextEmbeddingsModule
TypeScript API implementation of the useTextEmbeddings hook.
Reference
import {
TextEmbeddingsModule,
ALL_MINILM_L6_V2,
} from 'react-native-executorch';
// Creating an instance
const textEmbeddingsModule = new TextEmbeddingsModule();
// Loading the model
await textEmbeddingsModule.load(ALL_MINILM_L6_V2);
// Running the model
const embedding = await textEmbeddingsModule.forward('Hello World!');
Methods
Method | Type | Description |
---|---|---|
load | (model: { modelSource: ResourceSource; tokenizerSource: ResourceSource }, onDownloadProgressCallback?: (progress: number) => void): Promise<void> | Loads the model, where modelSource is a string that specifies the location of the model binary, tokenizerSource is a string that specifies the location of the tokenizer JSON file. |
forward | (input: string): Promise<number[]> | Executes the model's forward pass, where input is a text that will be embedded. |
onDownloadProgress | (callback: (downloadProgress: number) => void): any | Subscribe to the download progress event. |


Type definitions
type ResourceSource = string | number | object;
Loading the model
To load the model, use the load
method. It accepts an object:
model
- Object containing the model source and tokenizer source.
modelSource
- A string that specifies the location of the model binary.tokenizerSource
- A string that specifies the location of the tokenizer JSON file.
onDownloadProgressCallback
- (Optional) Function called on download progress.
This method returns a promise, which can resolve to an error or void.
For more information on loading resources, take a look at loading models page.
Running the model
To run the model, you can use the forward
method. It accepts one argument, which is the text you want to embed. The method returns a promise, which can resolve either to an error or an array of numbers representing the embedding.