diff --git a/.eslintrc.js b/.eslintrc.js index 35d2da64cc..b09ff37d23 100644 --- a/.eslintrc.js +++ b/.eslintrc.js @@ -63,7 +63,11 @@ module.exports = { customWordListFile: path.resolve(__dirname, '.cspell-wordlist.txt'), }, ], - 'camelcase': 'error', + // `properties: 'never'` lets the lowercase snake_case keys in `models` + // (e.g. `models.text_to_speech.kokoro_small`, mirroring the underlying + // `.pte` filenames) pass while still requiring camelCase for variable + // and function declarations. + 'camelcase': ['error', { properties: 'never' }], 'jsdoc/require-jsdoc': 'off', 'jsdoc/require-param': ['error', { checkDestructured: false }], 'jsdoc/check-param-names': ['error', { checkDestructured: false }], diff --git a/apps/bare-rn/App.tsx b/apps/bare-rn/App.tsx index b7e28658dc..cb6af0aa33 100644 --- a/apps/bare-rn/App.tsx +++ b/apps/bare-rn/App.tsx @@ -13,11 +13,7 @@ import { TouchableWithoutFeedback, View, } from 'react-native'; -import { - initExecutorch, - useLLM, - LLAMA3_2_1B_SPINQUANT, -} from 'react-native-executorch'; +import { models, initExecutorch, useLLM } from 'react-native-executorch'; import { BareResourceFetcher } from 'react-native-executorch-bare-resource-fetcher'; import { setConfig } from '@kesha-antonov/react-native-background-downloader'; import { SafeAreaProvider, SafeAreaView } from 'react-native-safe-area-context'; @@ -144,7 +140,9 @@ function App() { const textInputRef = useRef(null); const scrollViewRef = useRef(null); - const llm = useLLM({ model: LLAMA3_2_1B_SPINQUANT }); + const llm = useLLM({ + model: models.llm.lfm2_5_1_2b_instruct(), + }); // Alternatively, to use a custom local model, uncomment below: // const llm = useLLM({ model: { // modelSource: require('./assets/ai-models/smolLm2/smolLm2_135M/smolLm2_135M_bf16.pte'), diff --git a/apps/computer-vision/app/classification/index.tsx b/apps/computer-vision/app/classification/index.tsx index d45e0ddbf8..55a42f7422 100644 --- a/apps/computer-vision/app/classification/index.tsx +++ b/apps/computer-vision/app/classification/index.tsx @@ -1,16 +1,22 @@ import Spinner from '../../components/Spinner'; import { getImage } from '../../utils'; import { + models, useClassification, - EFFICIENTNET_V2_S, - EFFICIENTNET_V2_S_QUANTIZED, ClassificationModelSources, } from 'react-native-executorch'; import { ModelPicker, ModelOption } from '../../components/ModelPicker'; +const classification = models.classification; const MODELS: ModelOption[] = [ - { label: 'EfficientNet V2 S Quantized', value: EFFICIENTNET_V2_S_QUANTIZED }, - { label: 'EfficientNet V2 S', value: EFFICIENTNET_V2_S }, + { + label: 'EfficientNet V2 S Quantized', + value: classification.efficientnet_v2_s(), + }, + { + label: 'EfficientNet V2 S', + value: classification.efficientnet_v2_s({ quant: false }), + }, ]; import { View, StyleSheet, Image, Text, ScrollView } from 'react-native'; import { BottomBar } from '../../components/BottomBar'; @@ -22,7 +28,7 @@ import ErrorBanner from '../../components/ErrorBanner'; export default function ClassificationScreen() { const [selectedModel, setSelectedModel] = - useState(EFFICIENTNET_V2_S_QUANTIZED); + useState(classification.efficientnet_v2_s()); const [results, setResults] = useState<{ label: string; score: number }[]>( [] ); diff --git a/apps/computer-vision/app/instance_segmentation/index.tsx b/apps/computer-vision/app/instance_segmentation/index.tsx index f669c383d5..72a4c64506 100644 --- a/apps/computer-vision/app/instance_segmentation/index.tsx +++ b/apps/computer-vision/app/instance_segmentation/index.tsx @@ -3,16 +3,9 @@ import { BottomBar } from '../../components/BottomBar'; import { getImage } from '../../utils'; import { ModelPicker, ModelOption } from '../../components/ModelPicker'; import { + models, useInstanceSegmentation, - YOLO26N_SEG, - YOLO26S_SEG, - YOLO26M_SEG, - YOLO26L_SEG, - YOLO26X_SEG, - RF_DETR_NANO_SEG, InstanceSegmentationModelSources, - FASTSAM_S, - FASTSAM_X, } from 'react-native-executorch'; import { View, @@ -29,21 +22,28 @@ import ImageWithMasks, { DisplayInstance, } from '../../components/ImageWithMasks'; import { StatsBar } from '../../components/StatsBar'; +const instanceSegmentation = models.instance_segmentation; +const objectDetection = models.object_detection; const MODELS: ModelOption[] = [ - { label: 'Yolo26N', value: YOLO26N_SEG }, - { label: 'Yolo26S', value: YOLO26S_SEG }, - { label: 'Yolo26M', value: YOLO26M_SEG }, - { label: 'Yolo26L', value: YOLO26L_SEG }, - { label: 'Yolo26X', value: YOLO26X_SEG }, - { label: 'RF-DeTR Nano', value: RF_DETR_NANO_SEG }, - { label: 'FastSAM-S', value: FASTSAM_S }, - { label: 'FastSAM-X', value: FASTSAM_X }, + { label: 'Yolo26N', value: instanceSegmentation.yolo26n_seg() }, + { label: 'Yolo26S', value: instanceSegmentation.yolo26s_seg() }, + { label: 'Yolo26M', value: instanceSegmentation.yolo26m_seg() }, + { label: 'Yolo26L', value: instanceSegmentation.yolo26l_seg() }, + { label: 'Yolo26X', value: instanceSegmentation.yolo26x_seg() }, + { + label: 'RF-DeTR Nano', + value: instanceSegmentation.rf_detr_nano_seg(), + }, + { label: 'FastSAM-S', value: objectDetection.fastsam_s() }, + { label: 'FastSAM-X', value: objectDetection.fastsam_x() }, ]; export default function InstanceSegmentationScreen() { const [selectedModel, setSelectedModel] = - useState(YOLO26N_SEG); + useState( + instanceSegmentation.yolo26n_seg() + ); const [inferenceTime, setInferenceTime] = useState(null); const { setGlobalGenerating } = useContext(GeneratingContext); diff --git a/apps/computer-vision/app/object_detection/index.tsx b/apps/computer-vision/app/object_detection/index.tsx index ea4a9fc7b7..1ed3c136ba 100644 --- a/apps/computer-vision/app/object_detection/index.tsx +++ b/apps/computer-vision/app/object_detection/index.tsx @@ -3,15 +3,9 @@ import { BottomBar } from '../../components/BottomBar'; import { ModelPicker, ModelOption } from '../../components/ModelPicker'; import { getImage } from '../../utils'; import { + models, Detection, useObjectDetection, - RF_DETR_NANO, - SSDLITE_320_MOBILENET_V3_LARGE, - YOLO26N, - YOLO26S, - YOLO26M, - YOLO26L, - YOLO26X, ObjectDetectionModelSources, } from 'react-native-executorch'; import { View, StyleSheet, Image, Text } from 'react-native'; @@ -20,15 +14,22 @@ import React, { useContext, useEffect, useState } from 'react'; import { GeneratingContext } from '../../context'; import ScreenWrapper from '../../ScreenWrapper'; import { StatsBar } from '../../components/StatsBar'; +const objectDetection = models.object_detection; const MODELS: ModelOption[] = [ - { label: 'RF-DeTR Nano', value: RF_DETR_NANO }, - { label: 'SSDLite MobileNet', value: SSDLITE_320_MOBILENET_V3_LARGE }, - { label: 'YOLO26N', value: YOLO26N }, - { label: 'YOLO26S', value: YOLO26S }, - { label: 'YOLO26M', value: YOLO26M }, - { label: 'YOLO26L', value: YOLO26L }, - { label: 'YOLO26X', value: YOLO26X }, + { + label: 'RF-DeTR Nano', + value: objectDetection.rf_detr_nano(), + }, + { + label: 'SSDLite MobileNet', + value: objectDetection.ssdlite_320_mobilenet_v3_large(), + }, + { label: 'YOLO26N', value: objectDetection.yolo26n() }, + { label: 'YOLO26S', value: objectDetection.yolo26s() }, + { label: 'YOLO26M', value: objectDetection.yolo26m() }, + { label: 'YOLO26L', value: objectDetection.yolo26l() }, + { label: 'YOLO26X', value: objectDetection.yolo26x() }, ]; import ErrorBanner from '../../components/ErrorBanner'; @@ -41,7 +42,7 @@ export default function ObjectDetectionScreen() { height: number; }>(); const [selectedModel, setSelectedModel] = - useState(RF_DETR_NANO); + useState(objectDetection.rf_detr_nano()); const [inferenceTime, setInferenceTime] = useState(null); const model = useObjectDetection({ model: selectedModel }); diff --git a/apps/computer-vision/app/ocr/index.tsx b/apps/computer-vision/app/ocr/index.tsx index de4abcd400..b81b57326c 100644 --- a/apps/computer-vision/app/ocr/index.tsx +++ b/apps/computer-vision/app/ocr/index.tsx @@ -2,17 +2,7 @@ import Spinner from '../../components/Spinner'; import { BottomBar } from '../../components/BottomBar'; import { ModelPicker, ModelOption } from '../../components/ModelPicker'; import { getImage } from '../../utils'; -import { - useOCR, - OCR_ENGLISH, - OCR_GERMAN, - OCR_FRENCH, - OCR_SPANISH, - OCR_ITALIAN, - OCR_JAPANESE, - OCR_KOREAN, - OCRProps, -} from 'react-native-executorch'; +import { models, useOCR, OCRProps } from 'react-native-executorch'; import { View, StyleSheet, Image, Text, ScrollView } from 'react-native'; import ImageWithBboxes2 from '../../components/ImageWithOCRBboxes'; import React, { useContext, useEffect, useState } from 'react'; @@ -22,14 +12,16 @@ import { StatsBar } from '../../components/StatsBar'; type OCRModelSources = OCRProps['model']; +const ocr = models.ocr.craft; + const MODELS: ModelOption[] = [ - { label: 'English', value: OCR_ENGLISH }, - { label: 'German', value: OCR_GERMAN }, - { label: 'French', value: OCR_FRENCH }, - { label: 'Spanish', value: OCR_SPANISH }, - { label: 'Italian', value: OCR_ITALIAN }, - { label: 'Japanese', value: OCR_JAPANESE }, - { label: 'Korean', value: OCR_KOREAN }, + { label: 'English', value: ocr({ language: 'en' }) }, + { label: 'German', value: ocr({ language: 'de' }) }, + { label: 'French', value: ocr({ language: 'fr' }) }, + { label: 'Spanish', value: ocr({ language: 'es' }) }, + { label: 'Italian', value: ocr({ language: 'it' }) }, + { label: 'Japanese', value: ocr({ language: 'ja' }) }, + { label: 'Korean', value: ocr({ language: 'ko' }) }, ]; import ErrorBanner from '../../components/ErrorBanner'; @@ -41,8 +33,9 @@ export default function OCRScreen() { width: number; height: number; }>(); - const [selectedModel, setSelectedModel] = - useState(OCR_ENGLISH); + const [selectedModel, setSelectedModel] = useState( + ocr({ language: 'en' }) + ); const [inferenceTime, setInferenceTime] = useState(null); const model = useOCR({ diff --git a/apps/computer-vision/app/ocr_vertical/index.tsx b/apps/computer-vision/app/ocr_vertical/index.tsx index 8754ee8b5f..f1a015eb01 100644 --- a/apps/computer-vision/app/ocr_vertical/index.tsx +++ b/apps/computer-vision/app/ocr_vertical/index.tsx @@ -1,7 +1,7 @@ import Spinner from '../../components/Spinner'; import { BottomBar } from '../../components/BottomBar'; import { getImage } from '../../utils'; -import { useVerticalOCR, OCR_ENGLISH } from 'react-native-executorch'; +import { models, useVerticalOCR } from 'react-native-executorch'; import { View, StyleSheet, Image, Text, ScrollView } from 'react-native'; import ImageWithBboxes2 from '../../components/ImageWithOCRBboxes'; import React, { useContext, useEffect, useState } from 'react'; @@ -22,7 +22,7 @@ export default function VerticalOCRScreen() { const [error, setError] = useState(null); const model = useVerticalOCR({ - model: OCR_ENGLISH, + model: models.ocr.craft({ language: 'en' }), independentCharacters: true, }); diff --git a/apps/computer-vision/app/pose_estimation/index.tsx b/apps/computer-vision/app/pose_estimation/index.tsx index 3a07816e7e..4546b628fa 100644 --- a/apps/computer-vision/app/pose_estimation/index.tsx +++ b/apps/computer-vision/app/pose_estimation/index.tsx @@ -2,11 +2,11 @@ import Spinner from '../../components/Spinner'; import { BottomBar } from '../../components/BottomBar'; import { getImage } from '../../utils'; import { + models, usePoseEstimation, PoseDetections, RnExecutorchError, RnExecutorchErrorCode, - YOLO26N_POSE, } from 'react-native-executorch'; import { View, StyleSheet, Image, Text } from 'react-native'; import React, { useContext, useEffect, useState } from 'react'; @@ -31,7 +31,7 @@ export default function PoseEstimationScreen() { const [inferenceTime, setInferenceTime] = useState(null); const [layout, setLayout] = useState({ width: 0, height: 0 }); - const model = usePoseEstimation({ model: YOLO26N_POSE }); + const model = usePoseEstimation({ model: models.pose_estimation.yolo26n() }); const { setGlobalGenerating } = useContext(GeneratingContext); useEffect(() => { diff --git a/apps/computer-vision/app/segment_anything/index.tsx b/apps/computer-vision/app/segment_anything/index.tsx index 037a988327..b4101309c0 100644 --- a/apps/computer-vision/app/segment_anything/index.tsx +++ b/apps/computer-vision/app/segment_anything/index.tsx @@ -21,13 +21,10 @@ import { AlphaType, } from '@shopify/react-native-skia'; import { + models, useInstanceSegmentation, useImageEmbeddings, useTextEmbeddings, - FASTSAM_S, - FASTSAM_X, - CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED, - CLIP_VIT_BASE_PATCH32_TEXT, InstanceSegmentationModelSources, SegmentedInstance, FastSAMLabel, @@ -48,19 +45,20 @@ import ImageWithMasks, { } from '../../components/ImageWithMasks'; import { getImage } from '../../utils'; import ColorPalette from '../../colors'; +const objectDetection = models.object_detection; type PromptMode = 'point' | 'box' | 'text'; const MODELS: ModelOption[] = [ - { label: 'FastSAM-S', value: FASTSAM_S }, - { label: 'FastSAM-X', value: FASTSAM_X }, + { label: 'FastSAM-S', value: objectDetection.fastsam_s() }, + { label: 'FastSAM-X', value: objectDetection.fastsam_x() }, ]; export default function SegmentAnythingScreen() { const { setGlobalGenerating } = useContext(GeneratingContext); const [selectedModel, setSelectedModel] = - useState(FASTSAM_S); + useState(objectDetection.fastsam_s()); const [mode, setMode] = useState('point'); const [inferenceTime, setInferenceTime] = useState(null); @@ -78,9 +76,11 @@ export default function SegmentAnythingScreen() { useInstanceSegmentation({ model: selectedModel }); const clipImage = useImageEmbeddings({ - model: CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED, + model: models.image_embedding.clip_vit_base_patch32_image(), + }); + const clipText = useTextEmbeddings({ + model: models.text_embedding.clip_vit_base_patch32_text(), }); - const clipText = useTextEmbeddings({ model: CLIP_VIT_BASE_PATCH32_TEXT }); const skiaSource = useImage(imageUri || null); const [textPrompt, setTextPrompt] = useState(''); diff --git a/apps/computer-vision/app/semantic_segmentation/index.tsx b/apps/computer-vision/app/semantic_segmentation/index.tsx index ba998bca2a..f77c8de9c8 100644 --- a/apps/computer-vision/app/semantic_segmentation/index.tsx +++ b/apps/computer-vision/app/semantic_segmentation/index.tsx @@ -3,13 +3,7 @@ import { BottomBar } from '../../components/BottomBar'; import { ModelPicker, ModelOption } from '../../components/ModelPicker'; import { getImage } from '../../utils'; import { - DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED, - DEEPLAB_V3_RESNET50_QUANTIZED, - DEEPLAB_V3_RESNET101_QUANTIZED, - LRASPP_MOBILENET_V3_LARGE_QUANTIZED, - FCN_RESNET50_QUANTIZED, - FCN_RESNET101_QUANTIZED, - SELFIE_SEGMENTATION, + models, useSemanticSegmentation, SemanticSegmentationModelSources, } from 'react-native-executorch'; @@ -27,6 +21,7 @@ import { GeneratingContext } from '../../context'; import ScreenWrapper from '../../ScreenWrapper'; import { StatsBar } from '../../components/StatsBar'; import ErrorBanner from '../../components/ErrorBanner'; +const semanticSegmentation = models.semantic_segmentation; const numberToColor: number[][] = [ [255, 87, 51], // 0 Red @@ -55,21 +50,39 @@ const numberToColor: number[][] = [ const MODELS: ModelOption[] = [ { label: 'DeepLab MobileNet', - value: DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED, + value: semanticSegmentation.deeplab_v3_mobilenet_v3_large(), + }, + { + label: 'DeepLab ResNet50', + value: semanticSegmentation.deeplab_v3_resnet50(), + }, + { + label: 'DeepLab ResNet101', + value: semanticSegmentation.deeplab_v3_resnet101(), + }, + { + label: 'LRASPP MobileNet', + value: semanticSegmentation.lraspp_mobilenet_v3_large(), + }, + { + label: 'FCN ResNet50', + value: semanticSegmentation.fcn_resnet50(), + }, + { + label: 'FCN ResNet101', + value: semanticSegmentation.fcn_resnet101(), + }, + { + label: 'Selfie Segmentation', + value: semanticSegmentation.selfie_segmentation(), }, - { label: 'DeepLab ResNet50', value: DEEPLAB_V3_RESNET50_QUANTIZED }, - { label: 'DeepLab ResNet101', value: DEEPLAB_V3_RESNET101_QUANTIZED }, - { label: 'LRASPP MobileNet', value: LRASPP_MOBILENET_V3_LARGE_QUANTIZED }, - { label: 'FCN ResNet50', value: FCN_RESNET50_QUANTIZED }, - { label: 'FCN ResNet101', value: FCN_RESNET101_QUANTIZED }, - { label: 'Selfie Segmentation', value: SELFIE_SEGMENTATION }, ]; export default function SemanticSegmentationScreen() { const { setGlobalGenerating } = useContext(GeneratingContext); const [selectedModel, setSelectedModel] = useState( - DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED + semanticSegmentation.deeplab_v3_mobilenet_v3_large() ); const { diff --git a/apps/computer-vision/app/style_transfer/index.tsx b/apps/computer-vision/app/style_transfer/index.tsx index 8770087067..d8eda655f7 100644 --- a/apps/computer-vision/app/style_transfer/index.tsx +++ b/apps/computer-vision/app/style_transfer/index.tsx @@ -3,11 +3,8 @@ import { BottomBar } from '../../components/BottomBar'; import { ModelPicker, ModelOption } from '../../components/ModelPicker'; import { getImage } from '../../utils'; import { + models, useStyleTransfer, - STYLE_TRANSFER_CANDY_QUANTIZED, - STYLE_TRANSFER_MOSAIC_QUANTIZED, - STYLE_TRANSFER_RAIN_PRINCESS_QUANTIZED, - STYLE_TRANSFER_UDNIE_QUANTIZED, StyleTransferModelName, ResourceSource, } from 'react-native-executorch'; @@ -18,6 +15,7 @@ import React, { useContext, useEffect, useState } from 'react'; import { GeneratingContext } from '../../context'; import ScreenWrapper from '../../ScreenWrapper'; import { StatsBar } from '../../components/StatsBar'; +const styleTransfer = models.style_transfer; type StyleTransferModelSources = { modelName: StyleTransferModelName; @@ -25,16 +23,19 @@ type StyleTransferModelSources = { }; const MODELS: ModelOption[] = [ - { label: 'Candy', value: STYLE_TRANSFER_CANDY_QUANTIZED }, - { label: 'Mosaic', value: STYLE_TRANSFER_MOSAIC_QUANTIZED }, - { label: 'Rain Princess', value: STYLE_TRANSFER_RAIN_PRINCESS_QUANTIZED }, - { label: 'Udnie', value: STYLE_TRANSFER_UDNIE_QUANTIZED }, + { label: 'Candy', value: styleTransfer.candy() }, + { label: 'Mosaic', value: styleTransfer.mosaic() }, + { + label: 'Rain Princess', + value: styleTransfer.rain_princess(), + }, + { label: 'Udnie', value: styleTransfer.udnie() }, ]; import ErrorBanner from '../../components/ErrorBanner'; export default function StyleTransferScreen() { const [selectedModel, setSelectedModel] = useState( - STYLE_TRANSFER_CANDY_QUANTIZED + styleTransfer.candy() ); const model = useStyleTransfer({ model: selectedModel }); diff --git a/apps/computer-vision/app/text_to_image/index.tsx b/apps/computer-vision/app/text_to_image/index.tsx index 6af71227e9..47fce1e8b6 100644 --- a/apps/computer-vision/app/text_to_image/index.tsx +++ b/apps/computer-vision/app/text_to_image/index.tsx @@ -14,9 +14,8 @@ import React, { useContext, useEffect, useState } from 'react'; import { useSafeAreaInsets } from 'react-native-safe-area-context'; import Spinner from '../../components/Spinner'; import { + models, useTextToImage, - BK_SDM_TINY_VPRED_256, - BK_SDM_TINY_VPRED_512, TextToImageProps, } from 'react-native-executorch'; import { ModelPicker, ModelOption } from '../../components/ModelPicker'; @@ -26,12 +25,19 @@ import ProgressBar from '../../components/ProgressBar'; import { Ionicons } from '@expo/vector-icons'; import { StatsBar } from '../../components/StatsBar'; import ErrorBanner from '../../components/ErrorBanner'; +const imageGeneration = models.image_generation; type TextToImageModelSources = TextToImageProps['model']; const MODELS: ModelOption[] = [ - { label: 'BK-SDM 256', value: BK_SDM_TINY_VPRED_256 }, - { label: 'BK-SDM 512', value: BK_SDM_TINY_VPRED_512 }, + { + label: 'BK-SDM 256', + value: imageGeneration.bk_sdm_tiny_vpred_256(), + }, + { + label: 'BK-SDM 512', + value: imageGeneration.bk_sdm_tiny_vpred_512(), + }, ]; export default function TextToImageScreen() { @@ -42,7 +48,7 @@ export default function TextToImageScreen() { const [input, setInput] = useState(''); const [selectedModel, setSelectedModel] = useState( - BK_SDM_TINY_VPRED_256 + imageGeneration.bk_sdm_tiny_vpred_256() ); const [generationTime, setGenerationTime] = useState(null); diff --git a/apps/computer-vision/components/vision_camera/tasks/ClassificationTask.tsx b/apps/computer-vision/components/vision_camera/tasks/ClassificationTask.tsx index ef0046a297..e5b2f3ad3f 100644 --- a/apps/computer-vision/components/vision_camera/tasks/ClassificationTask.tsx +++ b/apps/computer-vision/components/vision_camera/tasks/ClassificationTask.tsx @@ -2,7 +2,7 @@ import React, { useCallback, useEffect, useRef, useState } from 'react'; import { StyleSheet, Text, View } from 'react-native'; import { Frame, useFrameOutput } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; -import { EFFICIENTNET_V2_S, useClassification } from 'react-native-executorch'; +import { models, useClassification } from 'react-native-executorch'; import { FRAME_TARGET_RESOLUTION, TaskProps } from './types'; type Props = Omit< @@ -19,7 +19,9 @@ export default function ClassificationTask({ onFpsChange, onErrorChange, }: Props) { - const model = useClassification({ model: EFFICIENTNET_V2_S }); + const model = useClassification({ + model: models.classification.efficientnet_v2_s(), + }); const [classResult, setClassResult] = useState({ label: '', score: 0 }); const lastFrameTimeRef = useRef(Date.now()); diff --git a/apps/computer-vision/components/vision_camera/tasks/InstanceSegmentationTask.tsx b/apps/computer-vision/components/vision_camera/tasks/InstanceSegmentationTask.tsx index 52251f6e3e..478cb25732 100644 --- a/apps/computer-vision/components/vision_camera/tasks/InstanceSegmentationTask.tsx +++ b/apps/computer-vision/components/vision_camera/tasks/InstanceSegmentationTask.tsx @@ -3,11 +3,8 @@ import { StyleSheet, Text, View } from 'react-native'; import { Frame, useFrameOutput } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; import { + models, SegmentedInstance, - YOLO26N_SEG, - RF_DETR_NANO_SEG, - FASTSAM_S, - FASTSAM_X, useInstanceSegmentation, CocoLabel, CocoLabelYolo, @@ -20,6 +17,8 @@ import { buildDisplayInstances, DisplayInstance, } from '../../../components/ImageWithMasks'; +const instanceSegmentation = models.instance_segmentation; +const objectDetection = models.object_detection; type InstSegModelId = | 'instanceSegmentationYolo26n' @@ -42,19 +41,19 @@ export default function InstanceSegmentationTask({ onErrorChange, }: Props) { const yolo26n = useInstanceSegmentation({ - model: YOLO26N_SEG, + model: instanceSegmentation.yolo26n_seg(), preventLoad: activeModel !== 'instanceSegmentationYolo26n', }); const rfdetr = useInstanceSegmentation({ - model: RF_DETR_NANO_SEG, + model: instanceSegmentation.rf_detr_nano_seg(), preventLoad: activeModel !== 'instanceSegmentationRfdetr', }); const fastsamS = useInstanceSegmentation({ - model: FASTSAM_S, + model: objectDetection.fastsam_s(), preventLoad: activeModel !== 'instanceSegmentationFastsamS', }); const fastsamX = useInstanceSegmentation({ - model: FASTSAM_X, + model: objectDetection.fastsam_x(), preventLoad: activeModel !== 'instanceSegmentationFastsamX', }); diff --git a/apps/computer-vision/components/vision_camera/tasks/OCRTask.tsx b/apps/computer-vision/components/vision_camera/tasks/OCRTask.tsx index 3dfa874b43..54e73161a1 100644 --- a/apps/computer-vision/components/vision_camera/tasks/OCRTask.tsx +++ b/apps/computer-vision/components/vision_camera/tasks/OCRTask.tsx @@ -2,7 +2,7 @@ import React, { useCallback, useEffect, useRef, useState } from 'react'; import { StyleSheet, View } from 'react-native'; import { Frame, useFrameOutput } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; -import { OCR_ENGLISH, OCRDetection, useOCR } from 'react-native-executorch'; +import { models, OCRDetection, useOCR } from 'react-native-executorch'; import Svg, { Polygon, Text as SvgText } from 'react-native-svg'; import { FRAME_TARGET_RESOLUTION, TaskProps } from './types'; @@ -19,7 +19,7 @@ export default function OCRTask({ onFpsChange, onErrorChange, }: Props) { - const model = useOCR({ model: OCR_ENGLISH }); + const model = useOCR({ model: models.ocr.craft({ language: 'en' }) }); const [detections, setDetections] = useState([]); const [imageSize, setImageSize] = useState({ width: 1, height: 1 }); const lastFrameTimeRef = useRef(Date.now()); diff --git a/apps/computer-vision/components/vision_camera/tasks/ObjectDetectionTask.tsx b/apps/computer-vision/components/vision_camera/tasks/ObjectDetectionTask.tsx index 992a8eaad0..e05de26105 100644 --- a/apps/computer-vision/components/vision_camera/tasks/ObjectDetectionTask.tsx +++ b/apps/computer-vision/components/vision_camera/tasks/ObjectDetectionTask.tsx @@ -3,16 +3,15 @@ import { StyleSheet, View } from 'react-native'; import { Frame, useFrameOutput } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; import { + models, Detection, - RF_DETR_NANO, - SSDLITE_320_MOBILENET_V3_LARGE, - YOLO26N, useObjectDetection, CocoLabel, CocoLabelYolo, } from 'react-native-executorch'; import BoundingBoxes from '../../BoundingBoxes'; import { FRAME_TARGET_RESOLUTION, TaskProps } from './types'; +const objectDetection = models.object_detection; type ObjModelId = | 'objectDetectionSsdlite' @@ -34,15 +33,15 @@ export default function ObjectDetectionTask({ onErrorChange, }: Props) { const ssdlite = useObjectDetection({ - model: SSDLITE_320_MOBILENET_V3_LARGE, + model: objectDetection.ssdlite_320_mobilenet_v3_large(), preventLoad: activeModel !== 'objectDetectionSsdlite', }); const rfdetr = useObjectDetection({ - model: RF_DETR_NANO, + model: objectDetection.rf_detr_nano(), preventLoad: activeModel !== 'objectDetectionRfdetr', }); const yolo26n = useObjectDetection({ - model: YOLO26N, + model: objectDetection.yolo26n(), preventLoad: activeModel !== 'objectDetectionYolo26n', }); diff --git a/apps/computer-vision/components/vision_camera/tasks/PoseEstimationTask.tsx b/apps/computer-vision/components/vision_camera/tasks/PoseEstimationTask.tsx index 476435643d..a357881da0 100644 --- a/apps/computer-vision/components/vision_camera/tasks/PoseEstimationTask.tsx +++ b/apps/computer-vision/components/vision_camera/tasks/PoseEstimationTask.tsx @@ -4,9 +4,9 @@ import { Frame, useFrameOutput } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; import Svg, { Circle, Line } from 'react-native-svg'; import { + models, usePoseEstimation, PoseDetections, - YOLO26N_POSE, } from 'react-native-executorch'; import { TaskProps } from './types'; import { COCO_SKELETON_CONNECTIONS } from '../../utils/cocoSkeleton'; @@ -29,7 +29,7 @@ export default function PoseEstimationTask({ onErrorChange, }: Props) { const poseModel = usePoseEstimation({ - model: YOLO26N_POSE, + model: models.pose_estimation.yolo26n(), preventLoad: activeModel !== 'poseEstimationYolo26n', }); diff --git a/apps/computer-vision/components/vision_camera/tasks/SegmentationTask.tsx b/apps/computer-vision/components/vision_camera/tasks/SegmentationTask.tsx index b06f2ff9d1..b88e457b23 100644 --- a/apps/computer-vision/components/vision_camera/tasks/SegmentationTask.tsx +++ b/apps/computer-vision/components/vision_camera/tasks/SegmentationTask.tsx @@ -2,16 +2,7 @@ import React, { useCallback, useEffect, useRef, useState } from 'react'; import { StyleSheet, View } from 'react-native'; import { Frame, useFrameOutput } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; -import { - DEEPLAB_V3_RESNET50_QUANTIZED, - DEEPLAB_V3_RESNET101_QUANTIZED, - DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED, - FCN_RESNET50_QUANTIZED, - FCN_RESNET101_QUANTIZED, - LRASPP_MOBILENET_V3_LARGE_QUANTIZED, - SELFIE_SEGMENTATION, - useSemanticSegmentation, -} from 'react-native-executorch'; +import { models, useSemanticSegmentation } from 'react-native-executorch'; import { AlphaType, Canvas, @@ -22,6 +13,7 @@ import { } from '@shopify/react-native-skia'; import { CLASS_COLORS } from '../../utils/colors'; import { FRAME_TARGET_RESOLUTION, TaskProps } from './types'; +const semanticSegmentation = models.semantic_segmentation; type SegModelId = | 'segmentationDeeplabResnet50' @@ -47,31 +39,31 @@ export default function SegmentationTask({ onErrorChange, }: Props) { const segDeeplabResnet50 = useSemanticSegmentation({ - model: DEEPLAB_V3_RESNET50_QUANTIZED, + model: semanticSegmentation.deeplab_v3_resnet50(), preventLoad: activeModel !== 'segmentationDeeplabResnet50', }); const segDeeplabResnet101 = useSemanticSegmentation({ - model: DEEPLAB_V3_RESNET101_QUANTIZED, + model: semanticSegmentation.deeplab_v3_resnet101(), preventLoad: activeModel !== 'segmentationDeeplabResnet101', }); const segDeeplabMobilenet = useSemanticSegmentation({ - model: DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED, + model: semanticSegmentation.deeplab_v3_mobilenet_v3_large(), preventLoad: activeModel !== 'segmentationDeeplabMobilenet', }); const segLraspp = useSemanticSegmentation({ - model: LRASPP_MOBILENET_V3_LARGE_QUANTIZED, + model: semanticSegmentation.lraspp_mobilenet_v3_large(), preventLoad: activeModel !== 'segmentationLraspp', }); const segFcnResnet50 = useSemanticSegmentation({ - model: FCN_RESNET50_QUANTIZED, + model: semanticSegmentation.fcn_resnet50(), preventLoad: activeModel !== 'segmentationFcnResnet50', }); const segFcnResnet101 = useSemanticSegmentation({ - model: FCN_RESNET101_QUANTIZED, + model: semanticSegmentation.fcn_resnet101(), preventLoad: activeModel !== 'segmentationFcnResnet101', }); const segSelfie = useSemanticSegmentation({ - model: SELFIE_SEGMENTATION, + model: semanticSegmentation.selfie_segmentation(), preventLoad: activeModel !== 'segmentationSelfie', }); diff --git a/apps/computer-vision/components/vision_camera/tasks/StyleTransferTask.tsx b/apps/computer-vision/components/vision_camera/tasks/StyleTransferTask.tsx index 6361970bfc..d5f8578272 100644 --- a/apps/computer-vision/components/vision_camera/tasks/StyleTransferTask.tsx +++ b/apps/computer-vision/components/vision_camera/tasks/StyleTransferTask.tsx @@ -2,11 +2,7 @@ import React, { useCallback, useEffect, useRef, useState } from 'react'; import { StyleSheet, View } from 'react-native'; import { Frame, useFrameOutput } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; -import { - STYLE_TRANSFER_CANDY, - STYLE_TRANSFER_MOSAIC, - useStyleTransfer, -} from 'react-native-executorch'; +import { models, useStyleTransfer } from 'react-native-executorch'; import { AlphaType, Canvas, @@ -16,6 +12,7 @@ import { SkImage, } from '@shopify/react-native-skia'; import { FRAME_TARGET_RESOLUTION, TaskProps } from './types'; +const styleTransfer = models.style_transfer; type StyleModelId = 'styleTransferCandy' | 'styleTransferMosaic'; @@ -34,11 +31,11 @@ export default function StyleTransferTask({ onErrorChange, }: Props) { const candy = useStyleTransfer({ - model: STYLE_TRANSFER_CANDY, + model: styleTransfer.candy(), preventLoad: activeModel !== 'styleTransferCandy', }); const mosaic = useStyleTransfer({ - model: STYLE_TRANSFER_MOSAIC, + model: styleTransfer.mosaic(), preventLoad: activeModel !== 'styleTransferMosaic', }); diff --git a/apps/llm/app/llm/index.tsx b/apps/llm/app/llm/index.tsx index 901b74de43..ed7d4a99c1 100644 --- a/apps/llm/app/llm/index.tsx +++ b/apps/llm/app/llm/index.tsx @@ -11,7 +11,7 @@ import { View, } from 'react-native'; import SendIcon from '../../assets/icons/send_icon.svg'; -import { useLLM, LLAMA3_2_1B_SPINQUANT } from 'react-native-executorch'; +import { models, useLLM } from 'react-native-executorch'; import { ModelPicker } from '../../components/ModelPicker'; import { LLM_MODELS, LLMModelSources } from '../../components/llmModels'; import PauseIcon from '../../assets/icons/pause_icon.svg'; @@ -43,7 +43,7 @@ function LLMScreen() { const [isTextInputFocused, setIsTextInputFocused] = useState(false); const [userInput, setUserInput] = useState(''); const [selectedModel, setSelectedModel] = useState( - LLAMA3_2_1B_SPINQUANT + models.llm.lfm2_5_1_2b_instruct() ); const textInputRef = useRef(null); const { setGlobalGenerating } = useContext(GeneratingContext); diff --git a/apps/llm/app/llm_structured_output/index.tsx b/apps/llm/app/llm_structured_output/index.tsx index aea47b8136..8150da4d6c 100644 --- a/apps/llm/app/llm_structured_output/index.tsx +++ b/apps/llm/app/llm_structured_output/index.tsx @@ -24,10 +24,10 @@ import { useLLMStats } from '../../hooks/useLLMStats'; import { StatsBar } from '../../components/StatsBar'; import ErrorBanner from '../../components/ErrorBanner'; import { + models, useLLM, fixAndValidateStructuredOutput, getStructuredOutputPrompt, - QWEN3_1_7B_QUANTIZED, } from 'react-native-executorch'; import { ModelPicker } from '../../components/ModelPicker'; import { LLM_MODELS, LLMModelSources } from '../../components/llmModels'; @@ -83,8 +83,9 @@ export default function LLMScreenWrapper() { function LLMScreen() { const [isTextInputFocused, setIsTextInputFocused] = useState(false); const [userInput, setUserInput] = useState(''); - const [selectedModel, setSelectedModel] = - useState(QWEN3_1_7B_QUANTIZED); + const [selectedModel, setSelectedModel] = useState( + models.llm.qwen3_1_7b() + ); const textInputRef = useRef(null); const { setGlobalGenerating } = useContext(GeneratingContext); diff --git a/apps/llm/app/llm_tool_calling/index.tsx b/apps/llm/app/llm_tool_calling/index.tsx index 2ef688ed69..f059d59793 100644 --- a/apps/llm/app/llm_tool_calling/index.tsx +++ b/apps/llm/app/llm_tool_calling/index.tsx @@ -17,11 +17,7 @@ import SWMIcon from '../../assets/icons/swm_icon.svg'; import SendIcon from '../../assets/icons/send_icon.svg'; import Spinner from '../../components/Spinner'; import ErrorBanner from '../../components/ErrorBanner'; -import { - useLLM, - DEFAULT_SYSTEM_PROMPT, - HAMMER2_1_1_5B_QUANTIZED, -} from 'react-native-executorch'; +import { models, useLLM, DEFAULT_SYSTEM_PROMPT } from 'react-native-executorch'; import { ModelPicker } from '../../components/ModelPicker'; import { LLM_MODELS, LLMModelSources } from '../../components/llmModels'; import PauseIcon from '../../assets/icons/pause_icon.svg'; @@ -55,7 +51,7 @@ function LLMToolCallingScreen() { const [hasCalendarPermission, setHasCalendarPermission] = useState(true); const [hasBrightnessPermission, setHasBrightnessPermission] = useState(true); const [selectedModel, setSelectedModel] = useState( - HAMMER2_1_1_5B_QUANTIZED + models.llm.hammer2_1_1_5b() ); const textInputRef = useRef(null); const { setGlobalGenerating } = useContext(GeneratingContext); diff --git a/apps/llm/app/multimodal_llm/index.tsx b/apps/llm/app/multimodal_llm/index.tsx index b7d6859ede..0de5004849 100644 --- a/apps/llm/app/multimodal_llm/index.tsx +++ b/apps/llm/app/multimodal_llm/index.tsx @@ -14,7 +14,7 @@ import { import { launchImageLibrary } from 'react-native-image-picker'; import { useIsFocused } from '@react-navigation/native'; import { useSafeAreaInsets } from 'react-native-safe-area-context'; -import { useLLM, LFM2_5_VL_1_6B_QUANTIZED } from 'react-native-executorch'; +import { models, useLLM } from 'react-native-executorch'; import SendIcon from '../../assets/icons/send_icon.svg'; import PauseIcon from '../../assets/icons/pause_icon.svg'; import ColorPalette from '../../colors'; @@ -50,7 +50,7 @@ function MultimodalLLMScreen() { const [error, setError] = useState(null); const vlm = useLLM({ - model: LFM2_5_VL_1_6B_QUANTIZED, + model: models.llm.lfm2_5_vl_1_6b(), }); const tokenCount = vlm.isReady ? vlm.getGeneratedTokenCount() : 0; const { stats, onMessageSend } = useLLMStats( diff --git a/apps/llm/app/privacy_filter/index.tsx b/apps/llm/app/privacy_filter/index.tsx index e6541dfe52..6f3e132bc1 100644 --- a/apps/llm/app/privacy_filter/index.tsx +++ b/apps/llm/app/privacy_filter/index.tsx @@ -10,12 +10,13 @@ import { import { useIsFocused } from '@react-navigation/native'; import { useSafeAreaInsets } from 'react-native-safe-area-context'; import { + models, PiiEntity, - PRIVACY_FILTER_NEMOTRON, - PRIVACY_FILTER_OPENAI, PrivacyFilterModelSources, usePrivacyFilter, } from 'react-native-executorch'; + +const privacyFilter = models.privacy_filter; import ColorPalette from '../../colors'; import { ModelOption, ModelPicker } from '../../components/ModelPicker'; import { @@ -46,16 +47,19 @@ Workstation MAC 3C:22:FB:8E:01:9A, IPv4 10.0.42.118, device IMEI 359888061234560 /* cspell:enable */ const MODEL_OPTIONS: ModelOption[] = [ - { label: 'OpenAI Privacy Filter (8 entities)', value: PRIVACY_FILTER_OPENAI }, + { + label: 'OpenAI Privacy Filter (8 entities)', + value: privacyFilter.openai(), + }, { label: 'OpenMed Nemotron (55 entities)', - value: PRIVACY_FILTER_NEMOTRON, + value: privacyFilter.nemotron(), }, ]; // Pick the right sample to display/run based on the active model. function sampleFor(model: PrivacyFilterModelSources): string { - return model.modelName === PRIVACY_FILTER_NEMOTRON.modelName + return model.modelName === privacyFilter.nemotron().modelName ? NEMOTRON_SAMPLE : OPENAI_SAMPLE; } @@ -98,7 +102,7 @@ function PrivacyFilterScreen() { const [runError, setRunError] = useState(null); const [inferenceMs, setInferenceMs] = useState(null); const [selectedModel, setSelectedModel] = useState( - PRIVACY_FILTER_OPENAI + privacyFilter.openai() ); const filter = usePrivacyFilter({ model: selectedModel }); diff --git a/apps/llm/app/voice_chat/index.tsx b/apps/llm/app/voice_chat/index.tsx index 23ab70bff4..5bffeceb31 100644 --- a/apps/llm/app/voice_chat/index.tsx +++ b/apps/llm/app/voice_chat/index.tsx @@ -13,15 +13,9 @@ import SWMIcon from '../../assets/icons/swm_icon.svg'; import Spinner from '../../components/Spinner'; import ErrorBanner from '../../components/ErrorBanner'; import { + models, useSpeechToText, useLLM, - QWEN3_0_6B_QUANTIZED, - QWEN3_1_7B_QUANTIZED, - LLAMA3_2_1B_SPINQUANT, - WHISPER_TINY_EN, - WHISPER_TINY_EN_QUANTIZED, - WHISPER_BASE_EN, - WHISPER_SMALL_EN, LLMProps, SpeechToTextProps, } from 'react-native-executorch'; @@ -41,16 +35,24 @@ type LLMModelSources = LLMProps['model']; type STTModelSources = SpeechToTextProps['model']; const LLM_MODELS: ModelOption[] = [ - { label: 'Qwen3 0.6B', value: QWEN3_0_6B_QUANTIZED }, - { label: 'Qwen3 1.7B', value: QWEN3_1_7B_QUANTIZED }, - { label: 'Llama 1B', value: LLAMA3_2_1B_SPINQUANT }, + { label: 'Qwen3 0.6B', value: models.llm.qwen3_0_6b() }, + { label: 'Qwen3 1.7B', value: models.llm.qwen3_1_7b() }, + { label: 'Llama 1B', value: models.llm.llama3_2_1b() }, ]; const STT_MODELS: ModelOption[] = [ - { label: 'Whisper Tiny', value: WHISPER_TINY_EN }, - { label: 'Whisper Tiny Q', value: WHISPER_TINY_EN_QUANTIZED }, - { label: 'Whisper Base', value: WHISPER_BASE_EN }, - { label: 'Whisper Small', value: WHISPER_SMALL_EN }, + { + label: 'Whisper Tiny', + value: models.speech_to_text.whisper_tiny_en(), + }, + { + label: 'Whisper Base', + value: models.speech_to_text.whisper_base_en(), + }, + { + label: 'Whisper Small', + value: models.speech_to_text.whisper_small_en(), + }, ]; export default function VoiceChatScreenWrapper() { @@ -63,10 +65,12 @@ function VoiceChatScreen() { const { bottom } = useSafeAreaInsets(); const [isRecording, setIsRecording] = useState(false); const [liveTranscription, setLiveTranscription] = useState(''); - const [selectedLLM, setSelectedLLM] = - useState(QWEN3_0_6B_QUANTIZED); - const [selectedSTT, setSelectedSTT] = - useState(WHISPER_TINY_EN); + const [selectedLLM, setSelectedLLM] = useState( + models.llm.qwen3_0_6b() + ); + const [selectedSTT, setSelectedSTT] = useState( + models.speech_to_text.whisper_tiny_en() + ); const [error, setError] = useState(null); const [recorder] = useState(() => new AudioRecorder()); diff --git a/apps/llm/components/llmModels.ts b/apps/llm/components/llmModels.ts index 593db478b3..1d80d7a395 100644 --- a/apps/llm/components/llmModels.ts +++ b/apps/llm/components/llmModels.ts @@ -1,101 +1,146 @@ import { - LLAMA3_2_1B, + models, LLAMA3_2_1B_QLORA, - LLAMA3_2_1B_SPINQUANT, - LLAMA3_2_3B, LLAMA3_2_3B_QLORA, - LLAMA3_2_3B_SPINQUANT, - QWEN3_0_6B, - QWEN3_0_6B_QUANTIZED, - QWEN3_1_7B, - QWEN3_1_7B_QUANTIZED, - QWEN3_4B, - QWEN3_4B_QUANTIZED, - HAMMER2_1_0_5B, - HAMMER2_1_0_5B_QUANTIZED, - HAMMER2_1_1_5B, - HAMMER2_1_1_5B_QUANTIZED, - HAMMER2_1_3B, - HAMMER2_1_3B_QUANTIZED, - SMOLLM2_1_135M, - SMOLLM2_1_135M_QUANTIZED, - SMOLLM2_1_360M, - SMOLLM2_1_360M_QUANTIZED, - SMOLLM2_1_1_7B, - SMOLLM2_1_1_7B_QUANTIZED, - QWEN2_5_0_5B, - QWEN2_5_0_5B_QUANTIZED, - QWEN2_5_1_5B, - QWEN2_5_1_5B_QUANTIZED, - QWEN2_5_3B, - QWEN2_5_3B_QUANTIZED, - PHI_4_MINI_4B, - PHI_4_MINI_4B_QUANTIZED, - LFM2_5_350M, - LFM2_5_350M_QUANTIZED, - LFM2_5_1_2B_INSTRUCT, - LFM2_5_1_2B_INSTRUCT_QUANTIZED, LLMProps, - QWEN3_5_0_8B_QUANTIZED, - QWEN3_5_2B_QUANTIZED, - BIELIK_V3_0_1_5B_QUANTIZED, - BIELIK_V3_0_1_5B, } from 'react-native-executorch'; import { ModelOption } from './ModelPicker'; +const llm = models.llm; export type LLMModelSources = LLMProps['model']; export const LLM_MODELS: ModelOption[] = [ // Llama 3.2 - { label: 'Llama 3.2 1B', value: LLAMA3_2_1B }, + { + label: 'Llama 3.2 1B', + value: llm.llama3_2_1b({ quant: false }), + }, { label: 'Llama 3.2 1B QLoRA', value: LLAMA3_2_1B_QLORA }, - { label: 'Llama 3.2 1B SpinQuant', value: LLAMA3_2_1B_SPINQUANT }, - { label: 'Llama 3.2 3B', value: LLAMA3_2_3B }, + { label: 'Llama 3.2 1B SpinQuant', value: llm.llama3_2_1b() }, + { + label: 'Llama 3.2 3B', + value: llm.llama3_2_3b({ quant: false }), + }, { label: 'Llama 3.2 3B QLoRA', value: LLAMA3_2_3B_QLORA }, - { label: 'Llama 3.2 3B SpinQuant', value: LLAMA3_2_3B_SPINQUANT }, + { label: 'Llama 3.2 3B SpinQuant', value: llm.llama3_2_3b() }, // Qwen3 - { label: 'Qwen3 0.6B', value: QWEN3_0_6B }, - { label: 'Qwen3 0.6B Quantized', value: QWEN3_0_6B_QUANTIZED }, - { label: 'Qwen3 1.7B', value: QWEN3_1_7B }, - { label: 'Qwen3 1.7B Quantized', value: QWEN3_1_7B_QUANTIZED }, - { label: 'Qwen3 4B', value: QWEN3_4B }, - { label: 'Qwen3 4B Quantized', value: QWEN3_4B_QUANTIZED }, + { + label: 'Qwen3 0.6B', + value: llm.qwen3_0_6b({ quant: false }), + }, + { label: 'Qwen3 0.6B Quantized', value: llm.qwen3_0_6b() }, + { + label: 'Qwen3 1.7B', + value: llm.qwen3_1_7b({ quant: false }), + }, + { label: 'Qwen3 1.7B Quantized', value: llm.qwen3_1_7b() }, + { label: 'Qwen3 4B', value: llm.qwen3_4b({ quant: false }) }, + { label: 'Qwen3 4B Quantized', value: llm.qwen3_4b() }, // Hammer 2.1 - { label: 'Hammer 2.1 0.5B', value: HAMMER2_1_0_5B }, - { label: 'Hammer 2.1 0.5B Quantized', value: HAMMER2_1_0_5B_QUANTIZED }, - { label: 'Hammer 2.1 1.5B', value: HAMMER2_1_1_5B }, - { label: 'Hammer 2.1 1.5B Quantized', value: HAMMER2_1_1_5B_QUANTIZED }, - { label: 'Hammer 2.1 3B', value: HAMMER2_1_3B }, - { label: 'Hammer 2.1 3B Quantized', value: HAMMER2_1_3B_QUANTIZED }, + { + label: 'Hammer 2.1 0.5B', + value: llm.hammer2_1_0_5b({ quant: false }), + }, + { + label: 'Hammer 2.1 0.5B Quantized', + value: llm.hammer2_1_0_5b(), + }, + { + label: 'Hammer 2.1 1.5B', + value: llm.hammer2_1_1_5b({ quant: false }), + }, + { + label: 'Hammer 2.1 1.5B Quantized', + value: llm.hammer2_1_1_5b(), + }, + { + label: 'Hammer 2.1 3B', + value: llm.hammer2_1_3b({ quant: false }), + }, + { + label: 'Hammer 2.1 3B Quantized', + value: llm.hammer2_1_3b(), + }, // SmolLM2 - { label: 'SmolLM2 135M', value: SMOLLM2_1_135M }, - { label: 'SmolLM2 135M Quantized', value: SMOLLM2_1_135M_QUANTIZED }, - { label: 'SmolLM2 360M', value: SMOLLM2_1_360M }, - { label: 'SmolLM2 360M Quantized', value: SMOLLM2_1_360M_QUANTIZED }, - { label: 'SmolLM2 1.7B', value: SMOLLM2_1_1_7B }, - { label: 'SmolLM2 1.7B Quantized', value: SMOLLM2_1_1_7B_QUANTIZED }, + { + label: 'SmolLM2 135M', + value: llm.smollm2_1_135m({ quant: false }), + }, + { + label: 'SmolLM2 135M Quantized', + value: llm.smollm2_1_135m(), + }, + { + label: 'SmolLM2 360M', + value: llm.smollm2_1_360m({ quant: false }), + }, + { + label: 'SmolLM2 360M Quantized', + value: llm.smollm2_1_360m(), + }, + { + label: 'SmolLM2 1.7B', + value: llm.smollm2_1_1_7b({ quant: false }), + }, + { + label: 'SmolLM2 1.7B Quantized', + value: llm.smollm2_1_1_7b(), + }, // Qwen2.5 - { label: 'Qwen2.5 0.5B', value: QWEN2_5_0_5B }, - { label: 'Qwen2.5 0.5B Quantized', value: QWEN2_5_0_5B_QUANTIZED }, - { label: 'Qwen2.5 1.5B', value: QWEN2_5_1_5B }, - { label: 'Qwen2.5 1.5B Quantized', value: QWEN2_5_1_5B_QUANTIZED }, - { label: 'Qwen2.5 3B', value: QWEN2_5_3B }, - { label: 'Qwen2.5 3B Quantized', value: QWEN2_5_3B_QUANTIZED }, + { + label: 'Qwen2.5 0.5B', + value: llm.qwen2_5_0_5b({ quant: false }), + }, + { + label: 'Qwen2.5 0.5B Quantized', + value: llm.qwen2_5_0_5b(), + }, + { + label: 'Qwen2.5 1.5B', + value: llm.qwen2_5_1_5b({ quant: false }), + }, + { + label: 'Qwen2.5 1.5B Quantized', + value: llm.qwen2_5_1_5b(), + }, + { + label: 'Qwen2.5 3B', + value: llm.qwen2_5_3b({ quant: false }), + }, + { label: 'Qwen2.5 3B Quantized', value: llm.qwen2_5_3b() }, // Qwen3.5 - { label: 'Qwen3.5 0.8B Quantized', value: QWEN3_5_0_8B_QUANTIZED }, - { label: 'Qwen3.5 2B Quantized', value: QWEN3_5_2B_QUANTIZED }, + { label: 'Qwen3.5 0.8B Quantized', value: llm.qwen3_5_0_8b() }, + { label: 'Qwen3.5 2B Quantized', value: llm.qwen3_5_2b() }, // Phi-4 - { label: 'Phi-4 Mini 4B', value: PHI_4_MINI_4B }, - { label: 'Phi-4 Mini 4B Quantized', value: PHI_4_MINI_4B_QUANTIZED }, + { + label: 'Phi-4 Mini 4B', + value: llm.phi_4_mini_4b({ quant: false }), + }, + { + label: 'Phi-4 Mini 4B Quantized', + value: llm.phi_4_mini_4b(), + }, // LFM2.5 - { label: 'LFM2.5 350M', value: LFM2_5_350M }, - { label: 'LFM2.5 350M Quantized', value: LFM2_5_350M_QUANTIZED }, - { label: 'LFM2.5 1.2B Instruct', value: LFM2_5_1_2B_INSTRUCT }, + { + label: 'LFM2.5 350M', + value: llm.lfm2_5_350m({ quant: false }), + }, + { label: 'LFM2.5 350M Quantized', value: llm.lfm2_5_350m() }, + { + label: 'LFM2.5 1.2B Instruct', + value: llm.lfm2_5_1_2b_instruct({ quant: false }), + }, { label: 'LFM2.5 1.2B Instruct Quantized', - value: LFM2_5_1_2B_INSTRUCT_QUANTIZED, + value: llm.lfm2_5_1_2b_instruct(), }, // Bielik v3.0 - { label: 'Bielik v3.0 1.5B', value: BIELIK_V3_0_1_5B }, - { label: 'Bielik v3.0 1.5B Quantized', value: BIELIK_V3_0_1_5B_QUANTIZED }, + { + label: 'Bielik v3.0 1.5B', + value: llm.bielik_v3_0_1_5b({ quant: false }), + }, + { + label: 'Bielik v3.0 1.5B Quantized', + value: llm.bielik_v3_0_1_5b(), + }, ]; diff --git a/apps/speech/screens/Quiz.tsx b/apps/speech/screens/Quiz.tsx index ae7cf69998..ffd574d96d 100644 --- a/apps/speech/screens/Quiz.tsx +++ b/apps/speech/screens/Quiz.tsx @@ -17,10 +17,7 @@ import Animated, { runOnJS, } from 'react-native-reanimated'; import { SafeAreaProvider, SafeAreaView } from 'react-native-safe-area-context'; -import { - KOKORO_AMERICAN_ENGLISH_MALE_SANTA, - useTextToSpeech, -} from 'react-native-executorch'; +import { models, useTextToSpeech } from 'react-native-executorch'; import { AudioManager, AudioContext, @@ -59,7 +56,7 @@ const createAudioBufferFromVector = ( export const Quiz = ({ onBack }: { onBack: () => void }) => { // --- Hooks & State --- - const model = useTextToSpeech(KOKORO_AMERICAN_ENGLISH_MALE_SANTA); + const model = useTextToSpeech(models.text_to_speech.kokoro.en_us.santa()); const [shuffledQuestions] = useState(() => shuffleArray(QUESTIONS)); const [currentIndex, setCurrentIndex] = useState(0); diff --git a/apps/speech/screens/SpeechToTextScreen.tsx b/apps/speech/screens/SpeechToTextScreen.tsx index dfd39c15b4..0c8a5a58f8 100644 --- a/apps/speech/screens/SpeechToTextScreen.tsx +++ b/apps/speech/screens/SpeechToTextScreen.tsx @@ -12,23 +12,29 @@ import { } from 'react-native'; import { SafeAreaProvider, SafeAreaView } from 'react-native-safe-area-context'; import { + models, useSpeechToText, - WHISPER_TINY_EN, - WHISPER_TINY_EN_QUANTIZED, - WHISPER_BASE_EN, - WHISPER_SMALL_EN, TranscriptionResult, SpeechToTextProps, } from 'react-native-executorch'; import { ModelPicker, ModelOption } from '../components/ModelPicker'; +const speechToText = models.speech_to_text; type STTModelSources = SpeechToTextProps['model']; const MODELS: ModelOption[] = [ - { label: 'Whisper Tiny', value: WHISPER_TINY_EN }, - { label: 'Whisper Tiny Q', value: WHISPER_TINY_EN_QUANTIZED }, - { label: 'Whisper Base', value: WHISPER_BASE_EN }, - { label: 'Whisper Small', value: WHISPER_SMALL_EN }, + { + label: 'Whisper Tiny', + value: speechToText.whisper_tiny_en(), + }, + { + label: 'Whisper Base', + value: speechToText.whisper_base_en(), + }, + { + label: 'Whisper Small', + value: speechToText.whisper_small_en(), + }, ]; import FontAwesome from '@expo/vector-icons/FontAwesome'; import { @@ -46,8 +52,9 @@ import ErrorBanner from '../components/ErrorBanner'; const isSimulator = DeviceInfo.isEmulatorSync(); export const SpeechToTextScreen = ({ onBack }: { onBack: () => void }) => { - const [selectedModel, setSelectedModel] = - useState(WHISPER_TINY_EN); + const [selectedModel, setSelectedModel] = useState( + speechToText.whisper_tiny_en() + ); const model = useSpeechToText({ model: selectedModel, @@ -109,14 +116,13 @@ export const SpeechToTextScreen = ({ onBack }: { onBack: () => void }) => { return; } - const uri = await getAudioFile(audioURL); // Reset previous states setTranscription(null); setLiveResult(null); - const audioContext = new AudioContext({ sampleRate: 16000 }); - try { + const uri = await getAudioFile(audioURL); + const audioContext = new AudioContext({ sampleRate: 16000 }); const decodedAudioData = await audioContext.decodeAudioData(uri); const audioBuffer = decodedAudioData.getChannelData(0); const start = Date.now(); @@ -326,6 +332,7 @@ export const SpeechToTextScreen = ({ onBack }: { onBack: () => void }) => { { const [displayText, setDisplayText] = useState(''); const [isTtsStreaming, setIsTtsStreaming] = useState(false); - const llm = useLLM({ model: LLAMA3_2_1B_QLORA }); - const tts = useTextToSpeech(KOKORO_AMERICAN_ENGLISH_FEMALE_HEART); + const llm = useLLM({ model: models.llm.llama3_2_1b() }); + const tts = useTextToSpeech(models.text_to_speech.kokoro.en_us.heart()); const processedLengthRef = useRef(0); const audioContextRef = useRef(null); diff --git a/apps/speech/screens/TextToSpeechScreen.tsx b/apps/speech/screens/TextToSpeechScreen.tsx index c9756b6aa6..198c40faf8 100644 --- a/apps/speech/screens/TextToSpeechScreen.tsx +++ b/apps/speech/screens/TextToSpeechScreen.tsx @@ -10,52 +10,35 @@ import { } from 'react-native'; import { SafeAreaProvider, SafeAreaView } from 'react-native-safe-area-context'; import { + models, useTextToSpeech, TextToSpeechModelConfig, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, - KOKORO_AMERICAN_ENGLISH_FEMALE_RIVER, - KOKORO_AMERICAN_ENGLISH_FEMALE_SARAH, - KOKORO_AMERICAN_ENGLISH_MALE_ADAM, - KOKORO_AMERICAN_ENGLISH_MALE_MICHAEL, - KOKORO_AMERICAN_ENGLISH_MALE_SANTA, - KOKORO_BRITISH_ENGLISH_FEMALE_EMMA, - KOKORO_BRITISH_ENGLISH_MALE_DANIEL, - KOKORO_FRENCH_FEMALE_SIWIS, - KOKORO_SPANISH_FEMALE_DORA, - KOKORO_SPANISH_MALE_ALEX, - KOKORO_ITALIAN_FEMALE_SARA, - KOKORO_ITALIAN_MALE_NICOLA, - KOKORO_PORTUGUESE_FEMALE_DORA, - KOKORO_PORTUGUESE_MALE_SANTA, - KOKORO_GERMAN_FEMALE_ANNA, - KOKORO_POLISH_MALE_MATEUSZ, - KOKORO_HINDI_FEMALE_ALPHA, - KOKORO_HINDI_MALE_OMEGA, - KOKORO_HINDI_MALE_PSI, } from 'react-native-executorch'; import { ModelPicker, ModelOption } from '../components/ModelPicker'; +const tts = models.text_to_speech.kokoro; + const VOICES: ModelOption[] = [ - { label: '🇺🇸 AF Heart', value: KOKORO_AMERICAN_ENGLISH_FEMALE_HEART }, - { label: '🇺🇸 AF River', value: KOKORO_AMERICAN_ENGLISH_FEMALE_RIVER }, - { label: '🇺🇸 AF Sarah', value: KOKORO_AMERICAN_ENGLISH_FEMALE_SARAH }, - { label: '🇺🇸 AM Adam', value: KOKORO_AMERICAN_ENGLISH_MALE_ADAM }, - { label: '🇺🇸 AM Michael', value: KOKORO_AMERICAN_ENGLISH_MALE_MICHAEL }, - { label: '🇺🇸 AM Santa', value: KOKORO_AMERICAN_ENGLISH_MALE_SANTA }, - { label: '🇬🇧 BF Emma', value: KOKORO_BRITISH_ENGLISH_FEMALE_EMMA }, - { label: '🇬🇧 BM Daniel', value: KOKORO_BRITISH_ENGLISH_MALE_DANIEL }, - { label: '🇫🇷 FF Siwis', value: KOKORO_FRENCH_FEMALE_SIWIS }, - { label: '🇪🇸 EF Dora', value: KOKORO_SPANISH_FEMALE_DORA }, - { label: '🇪🇸 EM Alex', value: KOKORO_SPANISH_MALE_ALEX }, - { label: '🇮🇹 IF Sara', value: KOKORO_ITALIAN_FEMALE_SARA }, - { label: '🇮🇹 IM Nicola', value: KOKORO_ITALIAN_MALE_NICOLA }, - { label: '🇵🇹 PF Dora', value: KOKORO_PORTUGUESE_FEMALE_DORA }, - { label: '🇵🇹 PM Santa', value: KOKORO_PORTUGUESE_MALE_SANTA }, - { label: '🇩🇪 DF Anna', value: KOKORO_GERMAN_FEMALE_ANNA }, - { label: '🇵🇱 PM Mateusz', value: KOKORO_POLISH_MALE_MATEUSZ }, - { label: '🇮🇳 HF Alpha', value: KOKORO_HINDI_FEMALE_ALPHA }, - { label: '🇮🇳 HM Omega', value: KOKORO_HINDI_MALE_OMEGA }, - { label: '🇮🇳 HM Psi', value: KOKORO_HINDI_MALE_PSI }, + { label: '🇺🇸 AF Heart', value: tts.en_us.heart() }, + { label: '🇺🇸 AF River', value: tts.en_us.river() }, + { label: '🇺🇸 AF Sarah', value: tts.en_us.sarah() }, + { label: '🇺🇸 AM Adam', value: tts.en_us.adam() }, + { label: '🇺🇸 AM Michael', value: tts.en_us.michael() }, + { label: '🇺🇸 AM Santa', value: tts.en_us.santa() }, + { label: '🇬🇧 BF Emma', value: tts.en_gb.emma() }, + { label: '🇬🇧 BM Daniel', value: tts.en_gb.daniel() }, + { label: '🇫🇷 FF Siwis', value: tts.fr.siwis() }, + { label: '🇪🇸 EF Dora', value: tts.es.dora() }, + { label: '🇪🇸 EM Alex', value: tts.es.alex() }, + { label: '🇮🇹 IF Sara', value: tts.it.sara() }, + { label: '🇮🇹 IM Nicola', value: tts.it.nicola() }, + { label: '🇵🇹 PF Dora', value: tts.pt.dora() }, + { label: '🇵🇹 PM Santa', value: tts.pt.santa() }, + { label: '🇩🇪 DF Anna', value: tts.de.anna() }, + { label: '🇵🇱 PM Mateusz', value: tts.pl.mateusz() }, + { label: '🇮🇳 HF Alpha', value: tts.hi.alpha() }, + { label: '🇮🇳 HM Omega', value: tts.hi.omega() }, + { label: '🇮🇳 HM Psi', value: tts.hi.psi() }, ]; import FontAwesome from '@expo/vector-icons/FontAwesome'; @@ -95,7 +78,7 @@ const createAudioBufferFromVector = ( export const TextToSpeechScreen = ({ onBack }: { onBack: () => void }) => { const [selectedSpeaker, setSelectedSpeaker] = - useState(KOKORO_AMERICAN_ENGLISH_FEMALE_HEART); + useState(tts.en_us.heart()); const model = useTextToSpeech(selectedSpeaker); @@ -236,6 +219,7 @@ export const TextToSpeechScreen = ({ onBack }: { onBack: () => void }) => { Enter text to synthesize (CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED); + useState( + models.image_embedding.clip_vit_base_patch32_image() + ); - const textModel = useTextEmbeddings({ model: CLIP_VIT_BASE_PATCH32_TEXT }); + const textModel = useTextEmbeddings({ + model: models.text_embedding.clip_vit_base_patch32_text(), + }); const imageModel = useImageEmbeddings({ model: selectedImageModel }); const [imageUri, setImageUri] = useState(null); @@ -249,6 +259,7 @@ function ClipEmbeddingsScreen() { (ALL_MINILM_L6_V2); + const [selectedModel, setSelectedModel] = useState( + textEmbedding.all_minilm_l6_v2() + ); const model = useTextEmbeddings({ model: selectedModel }); const [error, setError] = useState(null); @@ -189,6 +190,7 @@ function TextEmbeddingsScreen() { Try Your Sentence - + + ```bash npm install react-native-executorch + # For Expo projects, you need to install expo resource fetcher + npm install react-native-executorch-expo-resource-fetcher + npm install expo-file-system expo-asset + # For bare React Native projects, you need to install bare resource fetcher + npm install react-native-executorch-bare-resource-fetcher + npm install @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader ``` - + ```bash - pnpm add react-native-executorch + pnpm install react-native-executorch + # For Expo projects, you need to install expo resource fetcher + pnpm install react-native-executorch-expo-resource-fetcher + pnpm install expo-file-system expo-asset + # For bare React Native projects, you need to install bare resource fetcher + pnpm install react-native-executorch-bare-resource-fetcher + pnpm install @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader ``` - + ```bash yarn add react-native-executorch - ``` - - - - -### 2. Install a resource fetcher - -Pick the adapter that matches your project. We recommend the Expo adapter when your app uses Expo; use the bare adapter for projects without Expo. - -#### Expo projects - - - - - ```bash - npm install react-native-executorch-expo-resource-fetcher expo-file-system expo-asset - ``` - - - - - ```bash - pnpm add react-native-executorch-expo-resource-fetcher expo-file-system expo-asset - ``` - - - - - ```bash - yarn add react-native-executorch-expo-resource-fetcher expo-file-system expo-asset - ``` - - - - -#### Bare React Native projects - - - - - ```bash - npm install react-native-executorch-bare-resource-fetcher @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader - ``` - - - - - ```bash - pnpm add react-native-executorch-bare-resource-fetcher @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader - ``` - - - - - ```bash - yarn add react-native-executorch-bare-resource-fetcher @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader + # For Expo projects, you need to install expo resource fetcher + yarn add react-native-executorch-expo-resource-fetcher + yarn add expo-file-system expo-asset + # For bare React Native projects, you need to install bare resource fetcher + yarn add react-native-executorch-bare-resource-fetcher + yarn add @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader ``` @@ -160,29 +120,9 @@ Because we are using ExecuTorch under the hood, you won't be able to build iOS a Running the app with the library: - - - - ```bash - npm run -- -d - ``` - - - - - ```bash - pnpm -d - ``` - - - - - ```bash - yarn -d - ``` - - - +```bash +yarn -d +``` ## Supporting new models in React Native ExecuTorch diff --git a/docs/docs/01-fundamentals/02-loading-models.md b/docs/docs/01-fundamentals/02-loading-models.md index 28df1d8d6d..ffadd5dc08 100644 --- a/docs/docs/01-fundamentals/02-loading-models.md +++ b/docs/docs/01-fundamentals/02-loading-models.md @@ -2,9 +2,6 @@ title: Loading Models --- -import Tabs from '@theme/Tabs'; -import TabItem from '@theme/TabItem'; - There are three different methods available for loading model files, depending on their size and location. ## Prerequisites @@ -13,29 +10,10 @@ In our library, you can use two different resource fetching mechanisms. One is i To use the Expo adapter, please add these libraries: - - - - ```bash - npm install react-native-executorch-expo-resource-fetcher expo-file-system expo-asset - ``` - - - - - ```bash - pnpm add react-native-executorch-expo-resource-fetcher expo-file-system expo-asset - ``` - - - - - ```bash - yarn add react-native-executorch-expo-resource-fetcher expo-file-system expo-asset - ``` - - - +```bash +yarn add react-native-executorch-expo-resource-fetcher +yarn add expo-file-system expo-asset +``` and then add the following code in your React Native app: @@ -50,29 +28,10 @@ initExecutorch({ If you cannot use Expo in your project, proceed with the following steps: - - - - ```bash - npm install react-native-executorch-bare-resource-fetcher @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader - ``` - - - - - ```bash - pnpm add react-native-executorch-bare-resource-fetcher @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader - ``` - - - - - ```bash - yarn add react-native-executorch-bare-resource-fetcher @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader - ``` - - - +```bash +yarn add react-native-executorch-bare-resource-fetcher +yarn add @dr.pogodin/react-native-fs @kesha-antonov/react-native-background-downloader +``` and @@ -128,7 +87,6 @@ Our library offers out-of-the-box support for multiple models. To make things ea The following code snippet demonstrates how to load model and tokenizer files using `useLLM` hook: ```typescript -import { useLLM, LFM2_5_1_2B_INSTRUCT } from 'react-native-executorch'; - -const llm = useLLM({ model: LFM2_5_1_2B_INSTRUCT }); +import { models, useLLM } from 'react-native-executorch'; +const llm = useLLM({ model: models.llm.lfm2_5_1_2b_instruct() }); ``` diff --git a/docs/docs/03-hooks/01-natural-language-processing/useLLM.md b/docs/docs/03-hooks/01-natural-language-processing/useLLM.md index 7e6e4b17c2..7b1cb25158 100644 --- a/docs/docs/03-hooks/01-natural-language-processing/useLLM.md +++ b/docs/docs/03-hooks/01-natural-language-processing/useLLM.md @@ -44,9 +44,8 @@ Lower-end devices might not be able to fit LLMs into memory. We recommend using In order to load a model into the app, you need to run the following code: ```typescript -import { useLLM, LFM2_5_1_2B_INSTRUCT } from 'react-native-executorch'; - -const llm = useLLM({ model: LFM2_5_1_2B_INSTRUCT }); +import { models, useLLM } from 'react-native-executorch'; +const llm = useLLM({ model: models.llm.lfm2_5_1_2b_instruct() }); ```
@@ -92,7 +91,7 @@ You can use functions returned from this hooks in two manners: To perform chat completion you can use the [`generate`](../../06-api-reference/interfaces/LLMType.md#generate) function. The [`response`](../../06-api-reference/interfaces/LLMType.md#response) value is updated with each token as it's generated, and the function returns a promise that resolves to the complete response when generation finishes. ```tsx -const llm = useLLM({ model: LFM2_5_1_2B_INSTRUCT }); +const llm = useLLM({ model: models.llm.lfm2_5_1_2b_instruct() }); const handleGenerate = async () => { const chat: Message[] = [ @@ -152,7 +151,7 @@ const TOOL_DEFINITIONS: LLMTool[] = [ }, ]; -const llm = useLLM({ model: HAMMER2_1_1_5B }); +const llm = useLLM({ model: models.llm.hammer2_1_1_5b() }); const handleGenerate = () => { const chat: Message[] = [ @@ -226,13 +225,12 @@ Model presets expose an optional [`generationConfig`](../../06-api-reference/int ```tsx import { useEffect } from 'react'; import { + models, MessageCountContextStrategy, DEFAULT_SYSTEM_PROMPT, ToolCall, useLLM, - LFM2_5_1_2B_INSTRUCT, } from 'react-native-executorch'; - const TOOL_DEFINITIONS: LLMTool[] = [ { name: 'get_weather', @@ -266,7 +264,7 @@ const executeTool: (call: ToolCall) => Promise = async ( } }; -const llm = useLLM({ model: LFM2_5_1_2B_INSTRUCT }); +const llm = useLLM({ model: models.llm.lfm2_5_1_2b_instruct() }); const { configure } = llm; useEffect(() => { @@ -303,7 +301,7 @@ useEffect(() => { In order to send a message to the model, one can use the following code: ```tsx -const llm = useLLM({ model: LFM2_5_1_2B_INSTRUCT }); +const llm = useLLM({ model: models.llm.lfm2_5_1_2b_instruct() }); const send = () => { const message = 'Hi, who are you?'; @@ -348,7 +346,7 @@ const TOOL_DEFINITIONS: LLMTool[] = [ }, ]; -const llm = useLLM({ model: HAMMER2_1_1_5B }); +const llm = useLLM({ model: models.llm.hammer2_1_1_5b() }); useEffect(() => { llm.configure({ @@ -426,7 +424,7 @@ const responseSchemaWithZod = z.object({ currency: z.optional(z.string().meta({ description: 'Currency of offer.' })), }); -const llm = useLLM({ model: QWEN3_4B_QUANTIZED }); +const llm = useLLM({ model: models.llm.qwen3_4b() }); useEffect(() => { const formattingInstructions = getStructuredOutputPrompt(responseSchema); @@ -501,9 +499,8 @@ Some models support multimodal input — text and images together. To use them, ### Loading a VLM ```tsx -import { useLLM, LFM2_5_VL_1_6B_QUANTIZED } from 'react-native-executorch'; - -const llm = useLLM({ model: LFM2_5_VL_1_6B_QUANTIZED }); +import { models, useLLM } from 'react-native-executorch'; +const llm = useLLM({ model: models.llm.lfm2_5_vl_1_6b() }); ``` The `capabilities` field is already set on the model constant. You can also construct the model object explicitly: @@ -524,7 +521,7 @@ Passing `capabilities` unlocks the typed `media` argument on `sendMessage`. ### Sending a message with an image ```tsx -const llm = useLLM({ model: LFM2_5_VL_1_6B_QUANTIZED }); +const llm = useLLM({ model: models.llm.lfm2_5_vl_1_6b() }); const send = () => { llm.sendMessage('What is in this image?', { @@ -547,7 +544,7 @@ The `imagePath` should be a local file path on the device. You can also use `generate` directly by setting `mediaPath` on user messages: ```tsx -const llm = useLLM({ model: LFM2_5_VL_1_6B_QUANTIZED }); +const llm = useLLM({ model: models.llm.lfm2_5_vl_1_6b() }); const handleGenerate = async () => { const chat: Message[] = [ @@ -565,14 +562,14 @@ const handleGenerate = async () => { ## Available models -| Model Family | Sizes | Quantized | Capabilities | -| ------------------------------------------------------------------------------------------------------------------ | :-----------------: | :-------: | :----------: | -| [Hammer 2.1](https://huggingface.co/software-mansion/react-native-executorch-hammer-2.1) | 0.5B, 1.5B, 3B | ✅ | - | -| [Qwen 2.5](https://huggingface.co/software-mansion/react-native-executorch-qwen-2.5) | 0.5B, 1.5B, 3B | ✅ | - | -| [Qwen 3](https://huggingface.co/software-mansion/react-native-executorch-qwen-3) | 0.6B, 1.7B, 4B | ✅ | - | -| [Phi 4 Mini](https://huggingface.co/software-mansion/react-native-executorch-phi-4-mini) | 4B | ✅ | - | -| [SmolLM 2](https://huggingface.co/software-mansion/react-native-executorch-smolLm-2) | 135M, 360M, 1.7B | ✅ | - | -| [LLaMA 3.2](https://huggingface.co/software-mansion/react-native-executorch-llama-3.2) | 1B, 3B | ✅ | - | -| [LFM2.5](https://huggingface.co/software-mansion/react-native-executorch-lfm-2.5) | 350M, 1.2B, 1.6B-VL | ✅ | - | -| [LFM2.5-VL-450M](https://huggingface.co/software-mansion/react-native-executorch-lfm-2.5/tree/main/lfm2.5-VL-450M) | 450M | ✅ | vision | -| [LFM2.5-VL-1.6B](https://huggingface.co/software-mansion/react-native-executorch-lfm-2.5/tree/main/lfm2.5-VL-1.6B) | 1.6B | ✅ | vision | +| Model Family | Sizes | Quantized | Capabilities | +| ------------------------------------------------------------------------------------------ | :--------------------------: | :-------: | :----------: | +| [Hammer 2.1](https://huggingface.co/software-mansion/react-native-executorch-hammer-2.1) | 0.5B, 1.5B, 3B | ✅ | - | +| [Qwen 2.5](https://huggingface.co/software-mansion/react-native-executorch-qwen-2.5) | 0.5B, 1.5B, 3B | ✅ | - | +| [Qwen 3](https://huggingface.co/software-mansion/react-native-executorch-qwen-3) | 0.6B, 1.7B, 4B | ✅ | - | +| [Qwen 3.5](https://huggingface.co/software-mansion/react-native-executorch-qwen-3.5) | 0.8B, 2B | ✅ | - | +| [Phi 4 Mini](https://huggingface.co/software-mansion/react-native-executorch-phi-4-mini) | 4B | ✅ | - | +| [SmolLM 2](https://huggingface.co/software-mansion/react-native-executorch-smolLm-2) | 135M, 360M, 1.7B | ✅ | - | +| [LLaMA 3.2](https://huggingface.co/software-mansion/react-native-executorch-llama-3.2) | 1B, 3B | ✅ | - | +| [Bielik v3.0](https://huggingface.co/software-mansion/react-native-executorch-bielik-v3.0) | 1.5B | ✅ | - | +| [LFM2.5](https://huggingface.co/software-mansion/react-native-executorch-lfm-2.5) | 350M, 450M-VL, 1.2B, 1.6B-VL | ✅ | vision | diff --git a/docs/docs/03-hooks/01-natural-language-processing/usePrivacyFilter.md b/docs/docs/03-hooks/01-natural-language-processing/usePrivacyFilter.md index c0155dfbbf..97495f510b 100644 --- a/docs/docs/03-hooks/01-natural-language-processing/usePrivacyFilter.md +++ b/docs/docs/03-hooks/01-natural-language-processing/usePrivacyFilter.md @@ -32,12 +32,8 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```typescript -import { - usePrivacyFilter, - PRIVACY_FILTER_OPENAI, -} from 'react-native-executorch'; - -const model = usePrivacyFilter({ model: PRIVACY_FILTER_OPENAI }); +import { models, usePrivacyFilter } from 'react-native-executorch'; +const model = usePrivacyFilter({ model: models.privacy_filter.openai() }); try { const entities = await model.generate( @@ -89,14 +85,9 @@ Both built-in models ship with neutral, validity-only Viterbi decoding by defaul ```tsx import React, { useState } from 'react'; import { Button, Text, View, TextInput, ScrollView } from 'react-native'; -import { - usePrivacyFilter, - PRIVACY_FILTER_OPENAI, - PiiEntity, -} from 'react-native-executorch'; - +import { models, usePrivacyFilter, PiiEntity } from 'react-native-executorch'; export default function App() { - const model = usePrivacyFilter({ model: PRIVACY_FILTER_OPENAI }); + const model = usePrivacyFilter({ model: models.privacy_filter.openai() }); const [text, setText] = useState( 'My name is Sarah Chen and you can reach me at sarah.chen@example.com.' ); diff --git a/docs/docs/03-hooks/01-natural-language-processing/useSpeechToText.md b/docs/docs/03-hooks/01-natural-language-processing/useSpeechToText.md index 089b844eb0..39d0566af5 100644 --- a/docs/docs/03-hooks/01-natural-language-processing/useSpeechToText.md +++ b/docs/docs/03-hooks/01-natural-language-processing/useSpeechToText.md @@ -33,12 +33,12 @@ It is recommended to use models provided by us, which are available at our [Hugg You can obtain waveform from audio in any way most suitable to you, however in the snippet below we utilize [`react-native-audio-api`](https://docs.swmansion.com/react-native-audio-api/) library to process a `.mp3` file. ```typescript -import { useSpeechToText, WHISPER_TINY_EN } from 'react-native-executorch'; +import { models, useSpeechToText } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; import * as FileSystem from 'expo-file-system'; const model = useSpeechToText({ - model: WHISPER_TINY_EN, + model: models.speech_to_text.whisper_tiny_en(), }); const { uri } = await FileSystem.downloadAsync( @@ -92,10 +92,9 @@ Before running the model's [`transcribe`](../../06-api-reference/interfaces/Spee If you want to transcribe speech in languages other than English, use the multilingual version of Whisper. To generate the output in your desired language, pass the [`language`](../../06-api-reference/interfaces/DecodingOptions.md#language) option to the [`transcribe`](../../06-api-reference/interfaces/SpeechToTextType.md#transcribe) method. ```typescript -import { useSpeechToText, WHISPER_TINY } from 'react-native-executorch'; - +import { models, useSpeechToText } from 'react-native-executorch'; const model = useSpeechToText({ - model: WHISPER_TINY, + model: models.speech_to_text.whisper_tiny(), }); const transcription = await model.transcribe(spanishAudio, { language: 'es' }); @@ -143,8 +142,8 @@ const transcription = await model.transcribe(audioBuffer, { verbose: true }); import React, { useState } from 'react'; import { Button, Text, View } from 'react-native'; import { + models, useSpeechToText, - WHISPER_TINY_EN, TranscriptionResult, } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; @@ -152,7 +151,7 @@ import * as FileSystem from 'expo-file-system'; function App() { const model = useSpeechToText({ - model: WHISPER_TINY_EN, + model: models.speech_to_text.whisper_tiny_en(), }); const [transcription, setTranscription] = useState(null); @@ -220,12 +219,12 @@ function App() { ```tsx import React, { useEffect, useState, useRef } from 'react'; import { Text, Button, View, SafeAreaView } from 'react-native'; -import { useSpeechToText, WHISPER_TINY_EN } from 'react-native-executorch'; +import { models, useSpeechToText } from 'react-native-executorch'; import { AudioManager, AudioRecorder } from 'react-native-audio-api'; export default function App() { const model = useSpeechToText({ - model: WHISPER_TINY_EN, + model: models.speech_to_text.whisper_tiny_en(), }); const [transcribedText, setTranscribedText] = useState(''); diff --git a/docs/docs/03-hooks/01-natural-language-processing/useTextEmbeddings.md b/docs/docs/03-hooks/01-natural-language-processing/useTextEmbeddings.md index 09240d1e75..b9ba8c41b9 100644 --- a/docs/docs/03-hooks/01-natural-language-processing/useTextEmbeddings.md +++ b/docs/docs/03-hooks/01-natural-language-processing/useTextEmbeddings.md @@ -29,9 +29,10 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```typescript -import { useTextEmbeddings, ALL_MINILM_L6_V2 } from 'react-native-executorch'; - -const model = useTextEmbeddings({ model: ALL_MINILM_L6_V2 }); +import { models, useTextEmbeddings } from 'react-native-executorch'; +const model = useTextEmbeddings({ + model: models.text_embedding.all_minilm_l6_v2(), +}); try { const embedding = await model.forward('Hello World!'); @@ -64,8 +65,7 @@ To run the model, you can use the [`forward`](../../06-api-reference/interfaces/ ## Example ```typescript -import { useTextEmbeddings, ALL_MINILM_L6_V2 } from 'react-native-executorch'; - +import { models, useTextEmbeddings } from 'react-native-executorch'; const dotProduct = (a: number[], b: number[]) => a.reduce((sum, val, i) => sum + val * b[i], 0); @@ -77,7 +77,9 @@ const cosineSimilarity = (a: number[], b: number[]) => { }; function App() { - const model = useTextEmbeddings({ model: ALL_MINILM_L6_V2 }); + const model = useTextEmbeddings({ + model: models.text_embedding.all_minilm_l6_v2(), + }); // ... diff --git a/docs/docs/03-hooks/01-natural-language-processing/useTextToSpeech.md b/docs/docs/03-hooks/01-natural-language-processing/useTextToSpeech.md index e7b14defd0..fe0dd3b2ee 100644 --- a/docs/docs/03-hooks/01-natural-language-processing/useTextToSpeech.md +++ b/docs/docs/03-hooks/01-natural-language-processing/useTextToSpeech.md @@ -33,13 +33,10 @@ It is recommended to use models provided by us, which are available at our [Hugg You can play the generated waveform in any way most suitable to you; however, in the snippet below we utilize the react-native-audio-api library to play synthesized speech. ```typescript -import { - useTextToSpeech, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; +import { models, useTextToSpeech } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; -const model = useTextToSpeech(KOKORO_AMERICAN_ENGLISH_FEMALE_HEART); +const model = useTextToSpeech(models.text_to_speech.kokoro.en_us.heart()); const audioContext = new AudioContext({ sampleRate: 24000 }); @@ -114,14 +111,11 @@ Since `forward` and `stream` process the input, they might take a significant am ```tsx import React from 'react'; import { Button, View } from 'react-native'; -import { - useTextToSpeech, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; +import { models, useTextToSpeech } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; export default function App() { - const tts = useTextToSpeech(KOKORO_AMERICAN_ENGLISH_FEMALE_HEART); + const tts = useTextToSpeech(models.text_to_speech.kokoro.en_us.heart()); const generateAudio = async () => { const audioData = await tts.forward({ @@ -152,14 +146,11 @@ export default function App() { ```tsx import React, { useRef } from 'react'; import { Button, View } from 'react-native'; -import { - useTextToSpeech, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; +import { models, useTextToSpeech } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; export default function App() { - const tts = useTextToSpeech(KOKORO_AMERICAN_ENGLISH_FEMALE_HEART); + const tts = useTextToSpeech(models.text_to_speech.kokoro.en_us.heart()); const contextRef = useRef(new AudioContext({ sampleRate: 24000 })); @@ -199,13 +190,9 @@ If you already have a phoneme string obtained from an external source (e.g. the ```tsx import React from 'react'; import { Button, View } from 'react-native'; -import { - useTextToSpeech, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; - +import { models, useTextToSpeech } from 'react-native-executorch'; export default function App() { - const tts = useTextToSpeech(KOKORO_AMERICAN_ENGLISH_FEMALE_HEART); + const tts = useTextToSpeech(models.text_to_speech.kokoro.en_us.heart()); const synthesizePhonemes = async () => { // Example phonemes for "Hello" diff --git a/docs/docs/03-hooks/01-natural-language-processing/useTokenizer.md b/docs/docs/03-hooks/01-natural-language-processing/useTokenizer.md index aef466ade4..ba3516638e 100644 --- a/docs/docs/03-hooks/01-natural-language-processing/useTokenizer.md +++ b/docs/docs/03-hooks/01-natural-language-processing/useTokenizer.md @@ -29,9 +29,11 @@ We are using [Hugging Face Tokenizers](https://huggingface.co/docs/tokenizers/in ## High Level Overview ```typescript -import { useTokenizer, ALL_MINILM_L6_V2 } from 'react-native-executorch'; +import { models, useTokenizer } from 'react-native-executorch'; -const tokenizer = useTokenizer({ tokenizer: ALL_MINILM_L6_V2 }); +const tokenizer = useTokenizer({ + tokenizer: models.text_embedding.all_minilm_l6_v2(), +}); const text = 'Hello, world!'; @@ -52,7 +54,7 @@ try { `useTokenizer` takes [`TokenizerProps`](../../06-api-reference/interfaces/TokenizerProps.md) that consists of: -- `tokenizer` of type [`TokenizerProps`](../../06-api-reference/interfaces/TokenizerProps.md) containing [`tokenizerSource`](../../06-api-reference/interfaces/TokenizerProps.md#tokenizersource). +- `tokenizer` — an object containing [`tokenizerSource`](../../06-api-reference/interfaces/TokenizerProps.md#tokenizersource). - An optional flag [`preventLoad`](../../06-api-reference/interfaces/TokenizerProps.md#preventload) which prevents auto-loading of the model. You need more details? Check the following resources: @@ -67,10 +69,12 @@ You need more details? Check the following resources: ## Example ```typescript -import { useTokenizer, ALL_MINILM_L6_V2 } from 'react-native-executorch'; +import { models, useTokenizer } from 'react-native-executorch'; function App() { - const tokenizer = useTokenizer({ tokenizer: ALL_MINILM_L6_V2 }); + const tokenizer = useTokenizer({ + tokenizer: models.text_embedding.all_minilm_l6_v2(), + }); // ... diff --git a/docs/docs/03-hooks/01-natural-language-processing/useVAD.md b/docs/docs/03-hooks/01-natural-language-processing/useVAD.md index 81207dec07..01cf8cd4e3 100644 --- a/docs/docs/03-hooks/01-natural-language-processing/useVAD.md +++ b/docs/docs/03-hooks/01-natural-language-processing/useVAD.md @@ -18,12 +18,12 @@ It is recommended to use models provided by us, which are available at our [Hugg You can obtain waveform from audio in any way most suitable to you, however in the snippet below we utilize [`react-native-audio-api`](https://docs.swmansion.com/react-native-audio-api/) library to process a `.mp3` file. ```typescript -import { useVAD, FSMN_VAD } from 'react-native-executorch'; +import { models, useVAD } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; import * as FileSystem from 'expo-file-system'; const model = useVAD({ - model: FSMN_VAD, + model: models.vad.fsmn_vad(), }); const { uri } = await FileSystem.downloadAsync( @@ -76,13 +76,13 @@ Timestamps in returned speech segments, correspond to indices of input array (wa ```tsx import React from 'react'; import { Button, Text, SafeAreaView } from 'react-native'; -import { useVAD, FSMN_VAD } from 'react-native-executorch'; +import { models, useVAD } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; import * as FileSystem from 'expo-file-system'; export default function App() { const model = useVAD({ - model: FSMN_VAD, + model: models.vad.fsmn_vad(), }); const audioURL = 'https://some-audio-url.com/file.mp3'; diff --git a/docs/docs/03-hooks/02-computer-vision/useClassification.md b/docs/docs/03-hooks/02-computer-vision/useClassification.md index 53ec0901bd..7db709dd9a 100644 --- a/docs/docs/03-hooks/02-computer-vision/useClassification.md +++ b/docs/docs/03-hooks/02-computer-vision/useClassification.md @@ -20,9 +20,10 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```typescript -import { useClassification, EFFICIENTNET_V2_S } from 'react-native-executorch'; - -const model = useClassification({ model: EFFICIENTNET_V2_S }); +import { models, useClassification } from 'react-native-executorch'; +const model = useClassification({ + model: models.classification.efficientnet_v2_s(), +}); const imageUri = 'file::///Users/.../cute_puppy.png'; @@ -75,10 +76,11 @@ See the full guide: [VisionCamera Integration](./visioncamera-integration.md). ## Example ```typescript -import { useClassification, EFFICIENTNET_V2_S } from 'react-native-executorch'; - +import { models, useClassification } from 'react-native-executorch'; function App() { - const model = useClassification({ model: EFFICIENTNET_V2_S }); + const model = useClassification({ + model: models.classification.efficientnet_v2_s(), + }); // ... const imageUri = 'file:///Users/.../cute_puppy.png'; diff --git a/docs/docs/03-hooks/02-computer-vision/useImageEmbeddings.md b/docs/docs/03-hooks/02-computer-vision/useImageEmbeddings.md index df2442c6bd..13947a96f2 100644 --- a/docs/docs/03-hooks/02-computer-vision/useImageEmbeddings.md +++ b/docs/docs/03-hooks/02-computer-vision/useImageEmbeddings.md @@ -30,12 +30,10 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```typescript -import { - useImageEmbeddings, - CLIP_VIT_BASE_PATCH32_IMAGE, -} from 'react-native-executorch'; - -const model = useImageEmbeddings({ model: CLIP_VIT_BASE_PATCH32_IMAGE }); +import { models, useImageEmbeddings } from 'react-native-executorch'; +const model = useImageEmbeddings({ + model: models.image_embedding.clip_vit_base_patch32_image(), +}); try { const imageEmbedding = await model.forward('https://url-to-image.jpg'); diff --git a/docs/docs/03-hooks/02-computer-vision/useInstanceSegmentation.md b/docs/docs/03-hooks/02-computer-vision/useInstanceSegmentation.md index 129316cfee..d1728a3cf8 100644 --- a/docs/docs/03-hooks/02-computer-vision/useInstanceSegmentation.md +++ b/docs/docs/03-hooks/02-computer-vision/useInstanceSegmentation.md @@ -15,10 +15,9 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```typescript -import { useInstanceSegmentation, YOLO26N_SEG } from 'react-native-executorch'; - +import { models, useInstanceSegmentation } from 'react-native-executorch'; const model = useInstanceSegmentation({ - model: YOLO26N_SEG, + model: models.instance_segmentation.yolo26n_seg(), }); const imageUri = 'file:///Users/.../photo.jpg'; @@ -81,11 +80,10 @@ To run the model, use the [`forward`](../../06-api-reference/interfaces/Instance ## Example ```typescript -import { useInstanceSegmentation, YOLO26N_SEG } from 'react-native-executorch'; - +import { models, useInstanceSegmentation } from 'react-native-executorch'; function App() { const model = useInstanceSegmentation({ - model: YOLO26N_SEG, + model: models.instance_segmentation.yolo26n_seg(), }); const handleSegment = async () => { @@ -150,14 +148,15 @@ Instance segmentation models return a list of segmented instances. After `forwar ```typescript import { + models, useInstanceSegmentation, selectByPoint, selectByBox, selectByText, - FASTSAM_X, } from 'react-native-executorch'; - -const model = useInstanceSegmentation({ model: FASTSAM_X }); +const model = useInstanceSegmentation({ + model: models.object_detection.fastsam_x(), +}); try { const instances = await model.forward(imageUri); @@ -179,12 +178,6 @@ try { } ``` -For detailed API Reference for `selectByPoint`, `selectByBox`, and `selectByText` see their respective documentation pages: - -- [`selectByPoint` API Reference](../../06-api-reference/functions/selectByPoint.md) -- [`selectByBox` API Reference](../../06-api-reference/functions/selectByBox.md) -- [`selectByText` API Reference](../../06-api-reference/functions/selectByText.md) - :::tip Use FastSAM-S for faster performance on simple images with non-overlapping instances and FastSAM-X for better accuracy on complex scenes with many diff --git a/docs/docs/03-hooks/02-computer-vision/useOCR.md b/docs/docs/03-hooks/02-computer-vision/useOCR.md index 8f015e77a5..eaf9798fe5 100644 --- a/docs/docs/03-hooks/02-computer-vision/useOCR.md +++ b/docs/docs/03-hooks/02-computer-vision/useOCR.md @@ -16,10 +16,9 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```tsx -import { useOCR, OCR_ENGLISH } from 'react-native-executorch'; - +import { models, useOCR } from 'react-native-executorch'; function App() { - const model = useOCR({ model: OCR_ENGLISH }); + const model = useOCR({ model: models.ocr.craft({ language: 'en' }) }); // ... for (const ocrDetection of await model.forward('https://url-to-image.jpg')) { @@ -81,10 +80,9 @@ The `text` property contains the text recognized within detected text region. Th ## Example ```tsx -import { useOCR, OCR_ENGLISH } from 'react-native-executorch'; - +import { models, useOCR } from 'react-native-executorch'; function App() { - const model = useOCR({ model: OCR_ENGLISH }); + const model = useOCR({ model: models.ocr.craft({ language: 'en' }) }); const runModel = async () => { const ocrDetections = await model.forward('https://url-to-image.jpg'); diff --git a/docs/docs/03-hooks/02-computer-vision/useObjectDetection.md b/docs/docs/03-hooks/02-computer-vision/useObjectDetection.md index b5e0dfaf5e..317c00c3b7 100644 --- a/docs/docs/03-hooks/02-computer-vision/useObjectDetection.md +++ b/docs/docs/03-hooks/02-computer-vision/useObjectDetection.md @@ -16,13 +16,9 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```typescript -import { - useObjectDetection, - SSDLITE_320_MOBILENET_V3_LARGE, -} from 'react-native-executorch'; - +import { models, useObjectDetection } from 'react-native-executorch'; const model = useObjectDetection({ - model: SSDLITE_320_MOBILENET_V3_LARGE, + model: models.object_detection.ssdlite_320_mobilenet_v3_large(), }); const imageUri = 'file:///Users/.../photo.jpg'; @@ -84,11 +80,10 @@ To run the model, use the [`forward`](../../06-api-reference/interfaces/ObjectDe ## Example ```typescript -import { useObjectDetection, YOLO26N } from 'react-native-executorch'; - +import { models, useObjectDetection } from 'react-native-executorch'; function App() { const model = useObjectDetection({ - model: YOLO26N, + model: models.object_detection.yolo26n(), }); const handleDetect = async () => { diff --git a/docs/docs/03-hooks/02-computer-vision/usePoseEstimation.md b/docs/docs/03-hooks/02-computer-vision/usePoseEstimation.md index e31b928074..465a0ab6a6 100644 --- a/docs/docs/03-hooks/02-computer-vision/usePoseEstimation.md +++ b/docs/docs/03-hooks/02-computer-vision/usePoseEstimation.md @@ -16,10 +16,9 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```typescript -import { usePoseEstimation, YOLO26N_POSE } from 'react-native-executorch'; - +import { models, usePoseEstimation } from 'react-native-executorch'; const model = usePoseEstimation({ - model: YOLO26N_POSE, + model: models.pose_estimation.yolo26n(), }); const imageUri = 'file:///Users/.../photo.jpg'; @@ -94,11 +93,10 @@ The keypoint names available on each person are determined by the model's keypoi ## Example ```typescript -import { usePoseEstimation, YOLO26N_POSE } from 'react-native-executorch'; - +import { models, usePoseEstimation } from 'react-native-executorch'; function App() { const model = usePoseEstimation({ - model: YOLO26N_POSE, + model: models.pose_estimation.yolo26n(), }); const handleDetect = async () => { diff --git a/docs/docs/03-hooks/02-computer-vision/useSemanticSegmentation.md b/docs/docs/03-hooks/02-computer-vision/useSemanticSegmentation.md index dfc95317db..dd059cc4b6 100644 --- a/docs/docs/03-hooks/02-computer-vision/useSemanticSegmentation.md +++ b/docs/docs/03-hooks/02-computer-vision/useSemanticSegmentation.md @@ -16,13 +16,9 @@ It is recommended to use models provided by us which are available at our [Huggi ## High Level Overview ```typescript -import { - useSemanticSegmentation, - DEEPLAB_V3_RESNET50, -} from 'react-native-executorch'; - +import { models, useSemanticSegmentation } from 'react-native-executorch'; const model = useSemanticSegmentation({ - model: DEEPLAB_V3_RESNET50, + model: models.semantic_segmentation.deeplab_v3_resnet50(), }); const imageUri = 'file::///Users/.../cute_cat.png'; @@ -85,14 +81,13 @@ The return type is fully typed — TypeScript narrows it based on the labels you ```typescript import { + models, useSemanticSegmentation, - DEEPLAB_V3_RESNET50, DeeplabLabel, } from 'react-native-executorch'; - function App() { const model = useSemanticSegmentation({ - model: DEEPLAB_V3_RESNET50, + model: models.semantic_segmentation.deeplab_v3_resnet50(), }); const handleSegment = async () => { diff --git a/docs/docs/03-hooks/02-computer-vision/useStyleTransfer.md b/docs/docs/03-hooks/02-computer-vision/useStyleTransfer.md index 800a1cdc4f..f76693fdc4 100644 --- a/docs/docs/03-hooks/02-computer-vision/useStyleTransfer.md +++ b/docs/docs/03-hooks/02-computer-vision/useStyleTransfer.md @@ -16,12 +16,8 @@ It is recommended to use models provided by us which are available at our [Huggi ## High Level Overview ```typescript -import { - useStyleTransfer, - STYLE_TRANSFER_CANDY, -} from 'react-native-executorch'; - -const model = useStyleTransfer({ model: STYLE_TRANSFER_CANDY }); +import { models, useStyleTransfer } from 'react-native-executorch'; +const model = useStyleTransfer({ model: models.style_transfer.candy() }); const imageUri = 'file:///Users/.../cute_cat.png'; @@ -68,13 +64,9 @@ When `outputType` is `'url'`, the generated image is stored in your application' ## Example ```typescript -import { - useStyleTransfer, - STYLE_TRANSFER_CANDY, -} from 'react-native-executorch'; - +import { models, useStyleTransfer } from 'react-native-executorch'; function App() { - const model = useStyleTransfer({ model: STYLE_TRANSFER_CANDY }); + const model = useStyleTransfer({ model: models.style_transfer.candy() }); // Returns a file URI — easy to pass to const runWithUrl = async (imageUri: string) => { diff --git a/docs/docs/03-hooks/02-computer-vision/useTextToImage.md b/docs/docs/03-hooks/02-computer-vision/useTextToImage.md index 1968c46088..3ca063bf60 100644 --- a/docs/docs/03-hooks/02-computer-vision/useTextToImage.md +++ b/docs/docs/03-hooks/02-computer-vision/useTextToImage.md @@ -18,9 +18,10 @@ It is recommended to use models provided by us which are available at our [Huggi ## High Level Overview ```typescript -import { useTextToImage, BK_SDM_TINY_VPRED_256 } from 'react-native-executorch'; - -const model = useTextToImage({ model: BK_SDM_TINY_VPRED_256 }); +import { models, useTextToImage } from 'react-native-executorch'; +const model = useTextToImage({ + model: models.image_generation.bk_sdm_tiny_vpred_256(), +}); const input = 'a castle'; @@ -62,10 +63,11 @@ Larger imageSize values require significantly more memory to run the model. ## Example ```tsx -import { useTextToImage, BK_SDM_TINY_VPRED_256 } from 'react-native-executorch'; - +import { models, useTextToImage } from 'react-native-executorch'; function App() { - const model = useTextToImage({ model: BK_SDM_TINY_VPRED_256 }); + const model = useTextToImage({ + model: models.image_generation.bk_sdm_tiny_vpred_256(), + }); //... const input = 'a medieval castle by the sea shore'; diff --git a/docs/docs/03-hooks/02-computer-vision/useVerticalOCR.md b/docs/docs/03-hooks/02-computer-vision/useVerticalOCR.md index ff27b55e17..82c983d900 100644 --- a/docs/docs/03-hooks/02-computer-vision/useVerticalOCR.md +++ b/docs/docs/03-hooks/02-computer-vision/useVerticalOCR.md @@ -20,11 +20,10 @@ It is recommended to use models provided by us, which are available at our [Hugg ## High Level Overview ```tsx -import { useVerticalOCR, OCR_ENGLISH } from 'react-native-executorch'; - +import { models, useVerticalOCR } from 'react-native-executorch'; function App() { const model = useVerticalOCR({ - model: OCR_ENGLISH, + model: models.ocr.craft({ language: 'en' }), independentCharacters: true, }); @@ -89,11 +88,10 @@ The `text` property contains the text recognized within detected text region. Th ## Example ```tsx -import { useVerticalOCR, OCR_ENGLISH } from 'react-native-executorch'; - +import { models, useVerticalOCR } from 'react-native-executorch'; function App() { const model = useVerticalOCR({ - model: OCR_ENGLISH, + model: models.ocr.craft({ language: 'en' }), independentCharacters: true, }); diff --git a/docs/docs/03-hooks/02-computer-vision/visioncamera-integration.md b/docs/docs/03-hooks/02-computer-vision/visioncamera-integration.md index b96b7f5274..b421047552 100644 --- a/docs/docs/03-hooks/02-computer-vision/visioncamera-integration.md +++ b/docs/docs/03-hooks/02-computer-vision/visioncamera-integration.md @@ -78,17 +78,14 @@ import { useFrameOutput, } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; -import { - Detection, - useObjectDetection, - SSDLITE_320_MOBILENET_V3_LARGE, -} from 'react-native-executorch'; - +import { models, Detection, useObjectDetection } from 'react-native-executorch'; export default function App() { const { hasPermission, requestPermission } = useCameraPermission(); const devices = useCameraDevices(); const device = devices.find((d) => d.position === 'back'); - const model = useObjectDetection({ model: SSDLITE_320_MOBILENET_V3_LARGE }); + const model = useObjectDetection({ + model: models.object_detection.ssdlite_320_mobilenet_v3_large(), + }); const [detections, setDetections] = useState([]); const detRof = model.runOnFrame; @@ -211,11 +208,7 @@ import { useFrameOutput, } from 'react-native-vision-camera'; import { scheduleOnRN } from 'react-native-worklets'; -import { - ClassificationModule, - EFFICIENTNET_V2_S, -} from 'react-native-executorch'; - +import { models, ClassificationModule } from 'react-native-executorch'; export default function App() { const { hasPermission, requestPermission } = useCameraPermission(); const device = useCameraDevice('back'); @@ -227,7 +220,9 @@ export default function App() { }, [hasPermission, requestPermission]); useEffect(() => { - ClassificationModule.fromModelName(EFFICIENTNET_V2_S).then((module) => { + ClassificationModule.fromModelName( + models.classification.efficientnet_v2_s() + ).then((module) => { // () => module.runOnFrame is required — passing module.runOnFrame directly // would cause React to call it as a state initializer function setRunOnFrame(() => module.runOnFrame); diff --git a/docs/docs/03-hooks/03-executorch-bindings/useExecutorchModule.md b/docs/docs/03-hooks/03-executorch-bindings/useExecutorchModule.md index f51733307b..7429b4b60e 100644 --- a/docs/docs/03-hooks/03-executorch-bindings/useExecutorchModule.md +++ b/docs/docs/03-hooks/03-executorch-bindings/useExecutorchModule.md @@ -18,7 +18,6 @@ You can initialize the ExecuTorch module in your JavaScript application using th ```typescript import { useExecutorchModule } from 'react-native-executorch'; - const executorchModule = useExecutorchModule({ modelSource: require('../assets/models/model.pte'), }); @@ -64,14 +63,13 @@ First, import the necessary functions from the `react-native-executorch` package ```typescript import { + models, useExecutorchModule, - STYLE_TRANSFER_CANDY, ScalarType, } from 'react-native-executorch'; - // Initialize the executorch module with the predefined style transfer model. const executorchModule = useExecutorchModule({ - modelSource: STYLE_TRANSFER_CANDY, + modelSource: models.style_transfer.candy(), }); ``` diff --git a/docs/docs/04-typescript-api/01-natural-language-processing/LLMModule.md b/docs/docs/04-typescript-api/01-natural-language-processing/LLMModule.md index c1cf24a9fc..967625160c 100644 --- a/docs/docs/04-typescript-api/01-natural-language-processing/LLMModule.md +++ b/docs/docs/04-typescript-api/01-natural-language-processing/LLMModule.md @@ -13,11 +13,10 @@ TypeScript API implementation of the [useLLM](../../03-hooks/01-natural-language ## High Level Overview ```typescript -import { LLMModule, LFM2_5_1_2B_INSTRUCT } from 'react-native-executorch'; - +import { models, LLMModule } from 'react-native-executorch'; // Creating an instance and loading the model const llm = await LLMModule.fromModelName( - LFM2_5_1_2B_INSTRUCT, + models.llm.lfm2_5_1_2b_instruct(), (progress) => console.log(progress), (token) => console.log(token), (messages) => console.log(messages) @@ -44,7 +43,7 @@ Use the static [`fromModelName`](../../06-api-reference/classes/LLMModule.md#fro ```typescript const llm = await LLMModule.fromModelName( - LFM2_5_1_2B_INSTRUCT, // model config constant + models.llm.lfm2_5_1_2b_instruct(), // model config constant onDownloadProgress, // optional, progress 0–1 tokenCallback, // optional, called on every token messageHistoryCallback // optional, called when generation finishes @@ -122,10 +121,9 @@ Model presets expose an optional `generationConfig` that `LLMModule.fromModelNam Some models support multimodal input — text and images together. To use them, pass `capabilities` in the model object when calling [`fromModelName`](../../06-api-reference/classes/LLMModule.md#frommodelname): ```typescript -import { LLMModule, LFM2_5_VL_1_6B_QUANTIZED } from 'react-native-executorch'; - +import { models, LLMModule } from 'react-native-executorch'; const llm = await LLMModule.fromModelName( - LFM2_5_VL_1_6B_QUANTIZED, + models.llm.lfm2_5_vl_1_6b(), undefined, (token) => console.log(token) ); @@ -171,7 +169,6 @@ Use [`fromCustomModel`](../../06-api-reference/classes/LLMModule.md#fromcustommo ```typescript import { LLMModule } from 'react-native-executorch'; - const llm = await LLMModule.fromCustomModel( 'https://example.com/model.pte', 'https://example.com/tokenizer.json', diff --git a/docs/docs/04-typescript-api/01-natural-language-processing/PrivacyFilterModule.md b/docs/docs/04-typescript-api/01-natural-language-processing/PrivacyFilterModule.md index a862bce3bb..2df0f7dff0 100644 --- a/docs/docs/04-typescript-api/01-natural-language-processing/PrivacyFilterModule.md +++ b/docs/docs/04-typescript-api/01-natural-language-processing/PrivacyFilterModule.md @@ -12,13 +12,9 @@ TypeScript API implementation of the [usePrivacyFilter](../../03-hooks/01-natura ## High Level Overview ```typescript -import { - PrivacyFilterModule, - PRIVACY_FILTER_OPENAI, -} from 'react-native-executorch'; - +import { models, PrivacyFilterModule } from 'react-native-executorch'; const model = await PrivacyFilterModule.fromModelName( - PRIVACY_FILTER_OPENAI, + models.privacy_filter.openai(), (progress) => console.log(progress) ); diff --git a/docs/docs/04-typescript-api/01-natural-language-processing/SpeechToTextModule.md b/docs/docs/04-typescript-api/01-natural-language-processing/SpeechToTextModule.md index d4d8897e7c..de5d763db9 100644 --- a/docs/docs/04-typescript-api/01-natural-language-processing/SpeechToTextModule.md +++ b/docs/docs/04-typescript-api/01-natural-language-processing/SpeechToTextModule.md @@ -12,10 +12,9 @@ TypeScript API implementation of the [useSpeechToText](../../03-hooks/01-natural ## High Level Overview ```typescript -import { SpeechToTextModule, WHISPER_TINY_EN } from 'react-native-executorch'; - +import { models, SpeechToTextModule } from 'react-native-executorch'; const model = await SpeechToTextModule.fromModelName( - WHISPER_TINY_EN, + models.speech_to_text.whisper_tiny_en(), (progress) => { console.log(progress); } @@ -65,10 +64,9 @@ To run the model, you can use the [`transcribe`](../../06-api-reference/classes/ If you aim to obtain a transcription in other languages than English, use the multilingual version of whisper. To obtain the output text in your desired language, pass the [`DecodingOptions`](../../06-api-reference/interfaces/DecodingOptions.md) object with the [`language`](../../06-api-reference/interfaces/DecodingOptions.md#language) field set to your desired language code. ```typescript -import { SpeechToTextModule, WHISPER_TINY } from 'react-native-executorch'; - +import { models, SpeechToTextModule } from 'react-native-executorch'; const model = await SpeechToTextModule.fromModelName( - WHISPER_TINY, + models.speech_to_text.whisper_tiny(), (progress) => { console.log(progress); } @@ -118,14 +116,14 @@ const transcription = await model.transcribe(audioBuffer, { verbose: true }); ### Transcription ```tsx -import { SpeechToTextModule, WHISPER_TINY_EN } from 'react-native-executorch'; +import { models, SpeechToTextModule } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; import * as FileSystem from 'expo-file-system'; const transcribeAudio = async () => { // Initialize with the model config const model = await SpeechToTextModule.fromModelName( - WHISPER_TINY_EN, + models.speech_to_text.whisper_tiny_en(), (progress) => { console.log(progress); } @@ -164,12 +162,12 @@ const transcribeAudio = async () => { ### Streaming Transcription ```tsx -import { SpeechToTextModule, WHISPER_TINY_EN } from 'react-native-executorch'; +import { models, SpeechToTextModule } from 'react-native-executorch'; import { AudioManager, AudioRecorder } from 'react-native-audio-api'; // Load the model const model = await SpeechToTextModule.fromModelName( - WHISPER_TINY_EN, + models.speech_to_text.whisper_tiny_en(), (progress) => { console.log(progress); } diff --git a/docs/docs/04-typescript-api/01-natural-language-processing/TextEmbeddingsModule.md b/docs/docs/04-typescript-api/01-natural-language-processing/TextEmbeddingsModule.md index 054299290b..aa563c213d 100644 --- a/docs/docs/04-typescript-api/01-natural-language-processing/TextEmbeddingsModule.md +++ b/docs/docs/04-typescript-api/01-natural-language-processing/TextEmbeddingsModule.md @@ -12,14 +12,11 @@ TypeScript API implementation of the [useTextEmbeddings](../../03-hooks/01-natur ## High Level Overview ```typescript -import { - TextEmbeddingsModule, - ALL_MINILM_L6_V2, -} from 'react-native-executorch'; - +import { models, TextEmbeddingsModule } from 'react-native-executorch'; // Creating an instance and loading the model -const textEmbeddingsModule = - await TextEmbeddingsModule.fromModelName(ALL_MINILM_L6_V2); +const textEmbeddingsModule = await TextEmbeddingsModule.fromModelName( + models.text_embedding.all_minilm_l6_v2() +); // Running the model const embedding = await textEmbeddingsModule.forward('Hello World!'); diff --git a/docs/docs/04-typescript-api/01-natural-language-processing/TextToSpeechModule.md b/docs/docs/04-typescript-api/01-natural-language-processing/TextToSpeechModule.md index 2834b421f8..daf5cb735b 100644 --- a/docs/docs/04-typescript-api/01-natural-language-processing/TextToSpeechModule.md +++ b/docs/docs/04-typescript-api/01-natural-language-processing/TextToSpeechModule.md @@ -13,13 +13,9 @@ TypeScript API implementation of the [useTextToSpeech](../../03-hooks/01-natural ## High Level Overview ```typescript -import { - TextToSpeechModule, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; - +import { models, TextToSpeechModule } from 'react-native-executorch'; const model = await TextToSpeechModule.fromModelName( - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, + models.text_to_speech.kokoro.en_us.heart(), (progress) => console.log(progress) ); @@ -68,14 +64,11 @@ Since `forward` processes the entire input at once, it might take a significant ### Speech Synthesis ```typescript -import { - TextToSpeechModule, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; +import { models, TextToSpeechModule } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; const tts = await TextToSpeechModule.fromModelName( - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART + models.text_to_speech.kokoro.en_us.heart() ); const audioContext = new AudioContext({ sampleRate: 24000 }); @@ -98,14 +91,11 @@ try { ### Streaming Synthesis ```typescript -import { - TextToSpeechModule, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; +import { models, TextToSpeechModule } from 'react-native-executorch'; import { AudioContext } from 'react-native-audio-api'; const tts = await TextToSpeechModule.fromModelName( - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART + models.text_to_speech.kokoro.en_us.heart() ); const audioContext = new AudioContext({ sampleRate: 24000 }); @@ -136,13 +126,9 @@ try { If you already have a phoneme string (e.g., from an external library), you can use `forward` or `stream` with the `phonemize: false` flag to synthesize audio directly, skipping the internal phonemizer stage. ```typescript -import { - TextToSpeechModule, - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, -} from 'react-native-executorch'; - +import { models, TextToSpeechModule } from 'react-native-executorch'; const tts = await TextToSpeechModule.fromModelName( - KOKORO_AMERICAN_ENGLISH_FEMALE_HEART + models.text_to_speech.kokoro.en_us.heart() ); // Example phonemes for "ExecuTorch" diff --git a/docs/docs/04-typescript-api/01-natural-language-processing/TokenizerModule.md b/docs/docs/04-typescript-api/01-natural-language-processing/TokenizerModule.md index dffdfba867..f85178fe09 100644 --- a/docs/docs/04-typescript-api/01-natural-language-processing/TokenizerModule.md +++ b/docs/docs/04-typescript-api/01-natural-language-processing/TokenizerModule.md @@ -11,13 +11,12 @@ TypeScript API implementation of the [useTokenizer](../../03-hooks/01-natural-la ## High Level Overview ```typescript -import { TokenizerModule, ALL_MINILM_L6_V2 } from 'react-native-executorch'; - +import { models, TokenizerModule } from 'react-native-executorch'; // Creating an instance const tokenizerModule = new TokenizerModule(); // Load the tokenizer -await tokenizerModule.load(ALL_MINILM_L6_V2); +await tokenizerModule.load(models.text_embedding.all_minilm_l6_v2()); console.log('Tokenizer loaded'); // Get tokenizers vocabulary size diff --git a/docs/docs/04-typescript-api/01-natural-language-processing/VADModule.md b/docs/docs/04-typescript-api/01-natural-language-processing/VADModule.md index d32a7c3920..e9dd56710e 100644 --- a/docs/docs/04-typescript-api/01-natural-language-processing/VADModule.md +++ b/docs/docs/04-typescript-api/01-natural-language-processing/VADModule.md @@ -12,9 +12,8 @@ TypeScript API implementation of the [useVAD](../../03-hooks/01-natural-language ## High Level Overview ```typescript -import { VADModule, FSMN_VAD } from 'react-native-executorch'; - -const model = await VADModule.fromModelName(FSMN_VAD, (progress) => +import { models, VADModule } from 'react-native-executorch'; +const model = await VADModule.fromModelName(models.vad.fsmn_vad(), (progress) => console.log(progress) ); diff --git a/docs/docs/04-typescript-api/02-computer-vision/ClassificationModule.md b/docs/docs/04-typescript-api/02-computer-vision/ClassificationModule.md index 256e918123..8f7802686c 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/ClassificationModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/ClassificationModule.md @@ -12,16 +12,13 @@ TypeScript API implementation of the [useClassification](../../03-hooks/02-compu ## High Level Overview ```typescript -import { - ClassificationModule, - EFFICIENTNET_V2_S, -} from 'react-native-executorch'; - +import { models, ClassificationModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating and loading the module -const classificationModule = - await ClassificationModule.fromModelName(EFFICIENTNET_V2_S); +const classificationModule = await ClassificationModule.fromModelName( + models.classification.efficientnet_v2_s() +); // Running the model const classesWithProbabilities = await classificationModule.forward(imageUri); @@ -49,7 +46,6 @@ Use [`fromCustomModel`](../../06-api-reference/classes/ClassificationModule.md#f ```typescript import { ClassificationModule } from 'react-native-executorch'; - const MyLabels = { CAT: 0, DOG: 1, BIRD: 2 } as const; const classifier = await ClassificationModule.fromCustomModel( diff --git a/docs/docs/04-typescript-api/02-computer-vision/ImageEmbeddingsModule.md b/docs/docs/04-typescript-api/02-computer-vision/ImageEmbeddingsModule.md index 47eceef00a..132245a3f5 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/ImageEmbeddingsModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/ImageEmbeddingsModule.md @@ -12,14 +12,10 @@ TypeScript API implementation of the [useImageEmbeddings](../../03-hooks/02-comp ## High Level Overview ```typescript -import { - ImageEmbeddingsModule, - CLIP_VIT_BASE_PATCH32_IMAGE, -} from 'react-native-executorch'; - +import { models, ImageEmbeddingsModule } from 'react-native-executorch'; // Creating and loading the module const imageEmbeddingsModule = await ImageEmbeddingsModule.fromModelName( - CLIP_VIT_BASE_PATCH32_IMAGE + models.image_embedding.clip_vit_base_patch32_image() ); // Running the model diff --git a/docs/docs/04-typescript-api/02-computer-vision/InstanceSegmentationModule.md b/docs/docs/04-typescript-api/02-computer-vision/InstanceSegmentationModule.md index 6363de61f5..1403cfb21e 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/InstanceSegmentationModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/InstanceSegmentationModule.md @@ -11,16 +11,13 @@ TypeScript API implementation of the [useInstanceSegmentation](../../03-hooks/02 ## High Level Overview ```typescript -import { - InstanceSegmentationModule, - YOLO26N_SEG, -} from 'react-native-executorch'; - +import { models, InstanceSegmentationModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating an instance from a built-in model -const segmentation = - await InstanceSegmentationModule.fromModelName(YOLO26N_SEG); +const segmentation = await InstanceSegmentationModule.fromModelName( + models.instance_segmentation.yolo26n_seg() +); // Running the model const instances = await segmentation.forward(imageUri); @@ -44,13 +41,10 @@ Use [`fromModelName`](../../06-api-reference/classes/InstanceSegmentationModule. - `onDownloadProgress` (optional) - Callback to track download progress, receiving a value between 0 and 1. ```typescript -import { - InstanceSegmentationModule, - YOLO26N_SEG, -} from 'react-native-executorch'; - -const segmentation = - await InstanceSegmentationModule.fromModelName(YOLO26N_SEG); +import { models, InstanceSegmentationModule } from 'react-native-executorch'; +const segmentation = await InstanceSegmentationModule.fromModelName( + models.instance_segmentation.yolo26n_seg() +); ``` ### From a custom config diff --git a/docs/docs/04-typescript-api/02-computer-vision/OCRModule.md b/docs/docs/04-typescript-api/02-computer-vision/OCRModule.md index 1391982173..a1fac72f5c 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/OCRModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/OCRModule.md @@ -12,11 +12,13 @@ TypeScript API implementation of the [useOCR](../../03-hooks/02-computer-vision/ ## High Level Overview ```typescript -import { OCRModule, OCR_ENGLISH } from 'react-native-executorch'; +import { models, OCRModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating an instance and loading the model -const ocrModule = await OCRModule.fromModelName(OCR_ENGLISH); +const ocrModule = await OCRModule.fromModelName( + models.ocr.craft({ language: 'en' }) +); // Running the model const detections = await ocrModule.forward(imageUri); diff --git a/docs/docs/04-typescript-api/02-computer-vision/ObjectDetectionModule.md b/docs/docs/04-typescript-api/02-computer-vision/ObjectDetectionModule.md index 0d004e6752..4b1e19982f 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/ObjectDetectionModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/ObjectDetectionModule.md @@ -12,16 +12,12 @@ TypeScript API implementation of the [useObjectDetection](../../03-hooks/02-comp ## High Level Overview ```typescript -import { - ObjectDetectionModule, - SSDLITE_320_MOBILENET_V3_LARGE, -} from 'react-native-executorch'; - +import { models, ObjectDetectionModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating an instance and loading the model const objectDetectionModule = await ObjectDetectionModule.fromModelName( - SSDLITE_320_MOBILENET_V3_LARGE + models.object_detection.ssdlite_320_mobilenet_v3_large() ); // Running the model @@ -69,7 +65,6 @@ Use [`fromCustomModel`](../../06-api-reference/classes/ObjectDetectionModule.md# ```typescript import { ObjectDetectionModule } from 'react-native-executorch'; - const MyLabels = { BACKGROUND: 0, CAT: 1, DOG: 2 } as const; const detector = await ObjectDetectionModule.fromCustomModel( diff --git a/docs/docs/04-typescript-api/02-computer-vision/PoseEstimationModule.md b/docs/docs/04-typescript-api/02-computer-vision/PoseEstimationModule.md index bc32211b19..f8c2c7a173 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/PoseEstimationModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/PoseEstimationModule.md @@ -12,13 +12,13 @@ TypeScript API implementation of the [usePoseEstimation](../../03-hooks/02-compu ## High Level Overview ```typescript -import { PoseEstimationModule, YOLO26N_POSE } from 'react-native-executorch'; - +import { models, PoseEstimationModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating an instance and loading the model -const poseEstimationModule = - await PoseEstimationModule.fromModelName(YOLO26N_POSE); +const poseEstimationModule = await PoseEstimationModule.fromModelName( + models.pose_estimation.yolo26n() +); // Running the model const detections = await poseEstimationModule.forward(imageUri); @@ -72,7 +72,6 @@ Use [`fromCustomModel`](../../06-api-reference/classes/PoseEstimationModule.md#f ```typescript import { PoseEstimationModule } from 'react-native-executorch'; - const HandKeypoints = { WRIST: 0, THUMB_TIP: 1, diff --git a/docs/docs/04-typescript-api/02-computer-vision/SemanticSegmentationModule.md b/docs/docs/04-typescript-api/02-computer-vision/SemanticSegmentationModule.md index b248f2876e..fffe2a7ba1 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/SemanticSegmentationModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/SemanticSegmentationModule.md @@ -12,16 +12,13 @@ TypeScript API implementation of the [useSemanticSegmentation](../../03-hooks/02 ## High Level Overview ```typescript -import { - SemanticSegmentationModule, - DEEPLAB_V3_RESNET50, -} from 'react-native-executorch'; - +import { models, SemanticSegmentationModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating an instance from a built-in model -const segmentation = - await SemanticSegmentationModule.fromModelName(DEEPLAB_V3_RESNET50); +const segmentation = await SemanticSegmentationModule.fromModelName( + models.semantic_segmentation.deeplab_v3_resnet50() +); // Running the model const result = await segmentation.forward(imageUri); @@ -42,7 +39,7 @@ Use [`fromModelName`](../../06-api-reference/classes/SemanticSegmentationModule. ```typescript const segmentation = await SemanticSegmentationModule.fromModelName( - DEEPLAB_V3_RESNET50, + models.semantic_segmentation.deeplab_v3_resnet50(), (progress) => console.log(`Download: ${Math.round(progress * 100)}%`) ); ``` diff --git a/docs/docs/04-typescript-api/02-computer-vision/StyleTransferModule.md b/docs/docs/04-typescript-api/02-computer-vision/StyleTransferModule.md index 4c57716001..966cdff58b 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/StyleTransferModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/StyleTransferModule.md @@ -12,16 +12,13 @@ TypeScript API implementation of the [useStyleTransfer](../../03-hooks/02-comput ## High Level Overview ```typescript -import { - StyleTransferModule, - STYLE_TRANSFER_CANDY, -} from 'react-native-executorch'; - +import { models, StyleTransferModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating and loading the module -const styleTransferModule = - await StyleTransferModule.fromModelName(STYLE_TRANSFER_CANDY); +const styleTransferModule = await StyleTransferModule.fromModelName( + models.style_transfer.candy() +); // Running the model const generatedImageUrl = await styleTransferModule.forward(imageUri); diff --git a/docs/docs/04-typescript-api/02-computer-vision/TextToImageModule.md b/docs/docs/04-typescript-api/02-computer-vision/TextToImageModule.md index d6ade747bd..cf73eee019 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/TextToImageModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/TextToImageModule.md @@ -12,16 +12,12 @@ TypeScript API implementation of the [useTextToImage](../../03-hooks/02-computer ## High Level Overview ```typescript -import { - TextToImageModule, - BK_SDM_TINY_VPRED_256, -} from 'react-native-executorch'; - +import { models, TextToImageModule } from 'react-native-executorch'; const input = 'a castle'; // Creating an instance and loading the model const textToImageModule = await TextToImageModule.fromModelName( - BK_SDM_TINY_VPRED_256 + models.image_generation.bk_sdm_tiny_vpred_256() ); // Running the model diff --git a/docs/docs/04-typescript-api/02-computer-vision/VerticalOCRModule.md b/docs/docs/04-typescript-api/02-computer-vision/VerticalOCRModule.md index cc1cdba51d..59eaacfbb8 100644 --- a/docs/docs/04-typescript-api/02-computer-vision/VerticalOCRModule.md +++ b/docs/docs/04-typescript-api/02-computer-vision/VerticalOCRModule.md @@ -12,12 +12,13 @@ TypeScript API implementation of the [useVerticalOCR](../../03-hooks/02-computer ## High Level Overview ```typescript -import { VerticalOCRModule, OCR_ENGLISH } from 'react-native-executorch'; - +import { models, VerticalOCRModule } from 'react-native-executorch'; const imageUri = 'path/to/image.png'; // Creating an instance and loading the model -const verticalOCRModule = await VerticalOCRModule.fromModelName(OCR_ENGLISH); +const verticalOCRModule = await VerticalOCRModule.fromModelName( + models.ocr.craft({ language: 'en' }) +); // Running the model const detections = await verticalOCRModule.forward(imageUri); diff --git a/docs/docs/04-typescript-api/03-executorch-bindings/ExecutorchModule.md b/docs/docs/04-typescript-api/03-executorch-bindings/ExecutorchModule.md index 099379b333..252f7fa74a 100644 --- a/docs/docs/04-typescript-api/03-executorch-bindings/ExecutorchModule.md +++ b/docs/docs/04-typescript-api/03-executorch-bindings/ExecutorchModule.md @@ -15,12 +15,7 @@ For React applications, consider using the [`useExecutorchModule`](../../03-hook ## High Level Overview ```typescript -import { - ExecutorchModule, - STYLE_TRANSFER_CANDY, - ScalarType, -} from 'react-native-executorch'; - +import { models, ExecutorchModule, ScalarType } from 'react-native-executorch'; // Creating the input array const inputTensor = { dataPtr: new Float32Array(1 * 3 * 640 * 640), @@ -32,7 +27,7 @@ const inputTensor = { const model = new ExecutorchModule(); // Loading the model -await model.load(STYLE_TRANSFER_CANDY); +await model.load(models.style_transfer.candy()); // Running the forward method const output = await model.forward([inputTensor]); @@ -61,17 +56,12 @@ This example demonstrates the integration and usage of the ExecuTorch bindings w First, import the necessary functions from the `react-native-executorch` package and initialize the ExecuTorch module with the specified style transfer model. ```typescript -import { - ExecutorchModule, - STYLE_TRANSFER_CANDY, - ScalarType, -} from 'react-native-executorch'; - +import { models, ExecutorchModule, ScalarType } from 'react-native-executorch'; // Initialize the executorch module const executorchModule = new ExecutorchModule(); // Load the model with optional download progress callback -await executorchModule.load(STYLE_TRANSFER_CANDY, (progress) => { +await executorchModule.load(models.style_transfer.candy(), (progress) => { console.log(`Download progress: ${progress}%`); }); ``` diff --git a/docs/docs/05-utilities/04-error-handling.md b/docs/docs/05-utilities/04-error-handling.md index bf13b71668..3e1b9d9fe6 100644 --- a/docs/docs/05-utilities/04-error-handling.md +++ b/docs/docs/05-utilities/04-error-handling.md @@ -10,14 +10,13 @@ This example uses the `LLMModule`, and then tries to change its `generationConfi ```typescript import { + models, LLMModule, - LFM2_5_1_2B_INSTRUCT, RnExecutorchError, RnExecutorchErrorCode, } from 'react-native-executorch'; - const llm = await LLMModule.fromModelName( - LFM2_5_1_2B_INSTRUCT, + models.llm.lfm2_5_1_2b_instruct(), (progress) => console.log(progress), (token) => console.log(token), (messages) => console.log(messages) @@ -68,9 +67,7 @@ llm.delete(); ## Reference -All errors in React Native ExecuTorch inherit from `RnExecutorchError` and include a `code` property. The code is typed as `RnExecutorchErrorCode | number`: in practice you'll almost always see a member of the enum, but the codes are generated from a shared config into both the C++ and TS sources, and if those generated files drift the raw numeric value flows through unchanged. When switching on `err.code`, always include a `default` branch. - -Below is a comprehensive list of all possible errors, organized by category. +All errors in React Native ExecuTorch inherit from `RnExecutorchError` and include a `code` property from the `RnExecutorchErrorCode` enum. Below is a comprehensive list of all possible errors, organized by category. ### Module State Errors @@ -85,15 +82,15 @@ These errors occur when trying to perform operations on a model in an invalid st These errors occur when invalid configuration or input is provided. -| Error Code | Description | When It Occurs | How to Handle | -| ---------------------- | ------------------------------------ | --------------------------------------------------------------------------------------- | ------------------------------------------------------------- | -| `InvalidConfig` | Configuration parameters are invalid | Setting parameters outside valid ranges (e.g., `topp` outside [0, 1]) | Check parameter constraints and provide valid values | -| `InvalidUserInput` | Input provided to API is invalid | Passing empty arrays, null values, or malformed data to methods | Validate input before calling methods | -| `InvalidModelSource` | Model source type is invalid | Providing wrong type for model source (e.g., object when string expected) | Ensure model source matches expected type | -| `LanguageNotSupported` | Language not supported by model | Passing unsupported language to multilingual OCR or Speech-to-Text models | Use a supported language or different model | -| `PlatformNotSupported` | Current platform is not supported | Using features (e.g., camera frame processing) on an unsupported platform or OS version | Ensure you're running on a supported platform/OS version | -| `WrongDimensions` | Input tensor dimensions don't match | Providing input with incorrect shape for the model | Check model's expected input dimensions | -| `UnexpectedNumInputs` | Wrong number of inputs provided | Passing more or fewer inputs than model expects | Verify the expected model I/O contract in docs or source code | +| Error Code | Description | When It Occurs | How to Handle | +| ---------------------- | ------------------------------------ | --------------------------------------------------------------------------------------- | -------------------------------------------------------- | +| `InvalidConfig` | Configuration parameters are invalid | Setting parameters outside valid ranges (e.g., `topp` outside [0, 1]) | Check parameter constraints and provide valid values | +| `InvalidUserInput` | Input provided to API is invalid | Passing empty arrays, null values, or malformed data to methods | Validate input before calling methods | +| `InvalidModelSource` | Model source type is invalid | Providing wrong type for model source (e.g., object when string expected) | Ensure model source matches expected type | +| `LanguageNotSupported` | Language not supported by model | Passing unsupported language to multilingual OCR or Speech-to-Text models | Use a supported language or different model | +| `PlatformNotSupported` | Current platform is not supported | Using features (e.g., camera frame processing) on an unsupported platform or OS version | Ensure you're running on a supported platform/OS version | +| `WrongDimensions` | Input tensor dimensions don't match | Providing input with incorrect shape for the model | Check model's expected input dimensions | +| `UnexpectedNumInputs` | Wrong number of inputs provided | Passing more or fewer inputs than model expects | Match the number of inputs to model metadata | ### File Operations Errors @@ -135,12 +132,12 @@ These errors are specific to streaming transcription operations. These errors come from the ExecuTorch runtime during model execution. -| Error Code | Description | When It Occurs | How to Handle | -| -------------------- | -------------------------------- | ---------------------------------------------- | ----------------------------------------------------------- | -| `InvalidModelOutput` | Model output size unexpected | Model produces output of wrong size | Verify model's expected I/O contract in docs or source code | -| `ThreadPoolError` | Threadpool operation failed | Internal threading issue | Restart the model or app | -| `TokenizerError` | Tokenizer or tokenization failed | Tokenizer initialization or processing error | Check tokenizer files and model compatibility | -| `UnknownError` | Unexpected error occurred | 3rd-party library error or unhandled exception | Check logs for details, report if reproducible | +| Error Code | Description | When It Occurs | How to Handle | +| -------------------- | -------------------------------- | ---------------------------------------------- | ---------------------------------------------- | +| `InvalidModelOutput` | Model output size unexpected | Model produces output of wrong size | Verify model is compatible with the library | +| `ThreadPoolError` | Threadpool operation failed | Internal threading issue | Restart the model or app | +| `TokenizerError` | Tokenizer or tokenization failed | Tokenizer initialization or processing error | Check tokenizer files and model compatibility | +| `UnknownError` | Unexpected error occurred | 3rd-party library error or unhandled exception | Check logs for details, report if reproducible | ### ExecuTorch Runtime Errors diff --git a/docs/docs/05-utilities/model-registry.md b/docs/docs/05-utilities/model-registry.md index 02a74bbb13..83b9b80fd5 100644 --- a/docs/docs/05-utilities/model-registry.md +++ b/docs/docs/05-utilities/model-registry.md @@ -2,36 +2,142 @@ title: Model Registry --- -The [Model Registry](/react-native-executorch/docs/next/api-reference/variables/MODEL_REGISTRY) is a collection of all pre-configured model definitions shipped with React Native ExecuTorch. Each entry contains the model's name and all source URLs needed to download and run it, so you don't have to manage URLs manually. +The Model Registry is a typed, grouped index of every model shipped with React Native ExecuTorch. It removes the need to memorize per-model constant names: pick a capability group, pick a model, and optionally opt out of quantization or override the backend. -## Usage +```typescript +import { models } from 'react-native-executorch'; + +// Default (quantized when available, platform-default backend). +const llm = useLLM({ model: models.llm.llama3_2_3b() }); + +// Non-quantized variant. +const llmBase = useLLM({ model: models.llm.llama3_2_3b({ quant: false }) }); +``` + +Each leaf is a **function**. Call it (optionally with `{ quant, backend }`) to get the resolved model config. Accessors are not readable as values — this avoids a class of React state pitfalls (`useState` lazy-init, `useMemo`/`useCallback` deps), and pickers can fall back to plain `===` reference equality on the returned config. + +## Shape + +`models` is grouped by capability. Each leaf is a callable accessor. + +| Group | Examples | +| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `llm` | `llama3_2_3b`, `qwen3_4b`, `smollm2_1_1_7b`, `phi_4_mini_4b`, `bielik_v3_0_1_5b`, `lfm2_5_1_2b_instruct`, `lfm2_5_vl_1_6b`, `lfm2_5_vl_450m`, … | +| `classification` | `efficientnet_v2_s` | +| `privacy_filter` | `openai`, `nemotron` | +| `object_detection` | `ssdlite_320_mobilenet_v3_large`, `yolo26n` … `yolo26x`, `rf_detr_nano`, `fastsam_s`, `fastsam_x` | +| `pose_estimation` | `yolo26n` | +| `semantic_segmentation` | `deeplab_v3_resnet50`, `lraspp_mobilenet_v3_large`, `fcn_resnet101`, `selfie_segmentation`, … | +| `instance_segmentation` | `yolo26n_seg` … `yolo26x_seg`, `rf_detr_nano_seg` | +| `style_transfer` | `candy`, `mosaic`, `rain_princess`, `udnie` | +| `speech_to_text` | `whisper_tiny_en`, `whisper_base`, `whisper_small_en`, … | +| `text_to_speech` | nested by model family + language: `kokoro.en_us.{heart, river, sarah, adam, …}`, `kokoro.en_gb.{emma, daniel}`, `kokoro.fr.siwis`, `kokoro.es.{dora, alex}`, `kokoro.it.{sara, nicola}`, `kokoro.pt.{dora, santa}`, `kokoro.hi.{alpha, omega, psi}`, `kokoro.pl.mateusz`, `kokoro.de.anna` | +| `text_embedding` | `all_minilm_l6_v2`, `all_mpnet_base_v2`, `clip_vit_base_patch32_text`, … | +| `image_embedding` | `clip_vit_base_patch32_image` | +| `image_generation` | `bk_sdm_tiny_vpred_256`, `bk_sdm_tiny_vpred_512` | +| `vad` | `fsmn_vad` | +| `ocr` | nested by detector: `craft({ language: 'en' })` — see [§OCR](#ocr) below | + +## Options ```typescript -import { MODEL_REGISTRY, LFM2_5_1_2B_INSTRUCT } from 'react-native-executorch'; +type ModelOpts = { + quant?: boolean; // Pick the non-quantized variant when false. Defaults to the quantized variant when one is published. + backend?: B; // Explicit backend; the set of allowed values is per-model. +}; ``` -### Accessing a model directly +- `quant` defaults to the quantized variant for models that publish one (e.g. `llama3_2_3b` → SpinQuant, `efficientnet_v2_s` → int8). Pass `{ quant: false }` to get the full-precision variant. For models with a single variant, `quant` is accepted but has no effect. +- `backend` selects an explicit backend. The accessor's call signature is typed to exactly the backends the model ships with, so requesting one the model doesn't publish is a compile-time error (e.g. `models.llm.llama3_2_3b({ backend: 'coreml' })` does not type-check — Llama 3.2 is xnnpack-only). When `backend` is omitted, the platform-default applies: CoreML on iOS and XNNPACK on Android whenever the model ships that backend. Models that ship only one backend (e.g. xnnpack-only LLMs) use that one on both platforms. + +## Usage patterns -Every model config is exported as a standalone constant: +### Default model ```typescript -import { LFM2_5_1_2B_INSTRUCT } from 'react-native-executorch'; +import { models } from 'react-native-executorch'; -const llm = useLLM({ model: LFM2_5_1_2B_INSTRUCT }); +const llm = useLLM({ model: models.llm.llama3_2_3b() }); +const classifier = useClassification({ + model: models.classification.efficientnet_v2_s(), +}); +const stt = useSpeechToText({ + model: models.speech_to_text.whisper_tiny_en(), +}); ``` -### Listing all models +### Non-quantized variant -Use `MODEL_REGISTRY` to discover and enumerate all available models: +```typescript +const llm = useLLM({ model: models.llm.qwen3_4b({ quant: false }) }); +const classifier = useClassification({ + model: models.classification.efficientnet_v2_s({ quant: false }), +}); +``` + +### Explicit backend ```typescript -import { MODEL_REGISTRY } from 'react-native-executorch'; +// Force XNNPACK on iOS (overrides the CoreML default). +const detector = useObjectDetection({ + model: models.object_detection.rf_detr_nano({ backend: 'xnnpack' }), +}); + +// Combine `quant` and `backend`. +const styled = useStyleTransfer({ + model: models.style_transfer.candy({ backend: 'coreml', quant: false }), +}); +``` -// Get all model names -const names = Object.values(MODEL_REGISTRY.ALL_MODELS).map((m) => m.modelName); +### Text-to-speech -// Find models by name -const whisperModels = Object.values(MODEL_REGISTRY.ALL_MODELS).filter((m) => - m.modelName.includes('whisper') -); +`text_to_speech` is grouped by model family then by language code (`kokoro.en_us`, `kokoro.en_gb`, `kokoro.fr`, `kokoro.es`, `kokoro.it`, `kokoro.pt`, `kokoro.hi`, `kokoro.pl`, `kokoro.de`). Each leaf returns a complete Kokoro preset bundling the model, voice, and phonemizer — pass the whole result to `useTextToSpeech`. The `kokoro` level reserves room for a future TTS family without forcing a breaking rename. + +```typescript +import { models, useTextToSpeech } from 'react-native-executorch'; + +const tts = useTextToSpeech(models.text_to_speech.kokoro.en_us.heart()); +// Other languages: +// models.text_to_speech.kokoro.en_gb.emma() +// models.text_to_speech.kokoro.fr.siwis() +// models.text_to_speech.kokoro.pl.mateusz() ``` + +### OCR + +OCR is nested by detector family and parameterized by language. `craft` is the current pipeline (CRAFT detector + per-alphabet CRNN recognizer); future detectors land as siblings so the call site stays stable. + +```typescript +const ocr = useOcr({ + model: models.ocr.craft({ language: 'en' }), +}); +``` + +The `language` parameter is type-narrowed to supported tokens (`'en'`, `'es'`, `'ja'`, `'ko'`, …). See the OCR docs for the full list. + +### Direct imports still work + +Every model is also exported as a top-level constant. Either style is supported: + +```typescript +import { LFM2_5_1_2B_INSTRUCT, models } from 'react-native-executorch'; + +useLLM({ model: LFM2_5_1_2B_INSTRUCT }); +useLLM({ model: models.llm.lfm2_5_1_2b_instruct() }); +``` + +## Migration from the previous registry + +Earlier releases exposed `MODEL_REGISTRY` as an uppercase, dual-value/function shape. That has been replaced with a function-only, lowercase `models` export. + +```typescript +// Before +useLLM(MODEL_REGISTRY.LLM.LLAMA3_2_3B); +useLLM(MODEL_REGISTRY.LLM.LLAMA3_2_3B({ quant: false })); + +// After +useLLM({ model: models.llm.llama3_2_3b() }); +useLLM({ model: models.llm.llama3_2_3b({ quant: false }) }); +``` + +Individual constant imports (`LLAMA3_2_3B`, `WHISPER_TINY_EN`, …) are unchanged. diff --git a/docs/docs/08-resource-fetcher/02-custom-adapter.md b/docs/docs/08-resource-fetcher/02-custom-adapter.md index 36d25a888d..22773b3f47 100644 --- a/docs/docs/08-resource-fetcher/02-custom-adapter.md +++ b/docs/docs/08-resource-fetcher/02-custom-adapter.md @@ -13,7 +13,6 @@ import { ResourceFetcherAdapter, ResourceSource, } from 'react-native-executorch'; - interface ResourceFetcherAdapter { fetch( callback: (downloadProgress: number) => void, diff --git a/docs/versioned_docs/version-0.8.x/05-utilities/model-registry.md b/docs/versioned_docs/version-0.8.x/05-utilities/model-registry.md index 3b4241c986..7c15dc1205 100644 --- a/docs/versioned_docs/version-0.8.x/05-utilities/model-registry.md +++ b/docs/versioned_docs/version-0.8.x/05-utilities/model-registry.md @@ -2,7 +2,7 @@ title: Model Registry --- -The [Model Registry](/react-native-executorch/docs/next/api-reference/variables/MODEL_REGISTRY) is a collection of all pre-configured model definitions shipped with React Native ExecuTorch. Each entry contains the model's name and all source URLs needed to download and run it, so you don't have to manage URLs manually. +The [Model Registry](../api-reference/variables/MODEL_REGISTRY) is a collection of all pre-configured model definitions shipped with React Native ExecuTorch. Each entry contains the model's name and all source URLs needed to download and run it, so you don't have to manage URLs manually. ## Usage diff --git a/packages/react-native-executorch/src/constants/modelRegistry.ts b/packages/react-native-executorch/src/constants/modelRegistry.ts new file mode 100644 index 0000000000..34ed574224 --- /dev/null +++ b/packages/react-native-executorch/src/constants/modelRegistry.ts @@ -0,0 +1,571 @@ +import { Platform } from 'react-native'; +import * as M from './modelUrls'; +import * as OCR from './ocr/models'; +import { symbols } from './ocr/symbols'; +import { + KOKORO_AMERICAN_ENGLISH_FEMALE_HEART, + KOKORO_AMERICAN_ENGLISH_FEMALE_RIVER, + KOKORO_AMERICAN_ENGLISH_FEMALE_SARAH, + KOKORO_AMERICAN_ENGLISH_MALE_ADAM, + KOKORO_AMERICAN_ENGLISH_MALE_MICHAEL, + KOKORO_AMERICAN_ENGLISH_MALE_SANTA, + KOKORO_BRITISH_ENGLISH_FEMALE_EMMA, + KOKORO_BRITISH_ENGLISH_MALE_DANIEL, + KOKORO_FRENCH_FEMALE_SIWIS, + KOKORO_SPANISH_FEMALE_DORA, + KOKORO_SPANISH_MALE_ALEX, + KOKORO_ITALIAN_FEMALE_SARA, + KOKORO_ITALIAN_MALE_NICOLA, + KOKORO_PORTUGUESE_FEMALE_DORA, + KOKORO_PORTUGUESE_MALE_SANTA, + KOKORO_HINDI_FEMALE_ALPHA, + KOKORO_HINDI_MALE_OMEGA, + KOKORO_HINDI_MALE_PSI, + KOKORO_POLISH_MALE_MATEUSZ, + KOKORO_GERMAN_FEMALE_ANNA, +} from './tts/voices'; +import { TextToSpeechModelConfig } from '../types/tts'; + +/** + * Backend options accepted by `models` accessors. + * + * The set of backends a particular model can be loaded with is encoded in + * its accessor's call signature — e.g. `models.llm.llama3_2_3b` only accepts + * `'xnnpack'`, while `models.object_detection.rf_detr_nano` accepts + * `'xnnpack' | 'coreml'`. Passing a backend a model doesn't ship is a + * compile-time error. + * @category Utils + */ +export type Backend = 'xnnpack' | 'coreml' | 'vulkan' | 'qnn'; + +/** + * Options for a `models` accessor call. + * @typeParam B - Subset of {@link Backend} that the accessor actually supports. + * @category Utils + */ +export type ModelOpts = { + /** Pick the non-quantized variant when `false`. Defaults to the quantized variant when one is published. */ + quant?: boolean; + /** Explicit backend; defaults to the platform-preferred backend for the model. */ + backend?: B; +}; + +// Accessors are functions; calling with no opts returns the platform default. +type Accessor = ( + opts?: ModelOpts +) => C; + +type BackendCell = { + base?: { modelName: string }; + quant?: { modelName: string }; +}; +type AnyVariantMap = Partial>; +type PlatformDefaults = { + ios?: B; + android?: B; + /** Fallback when no platform-specific default is set. */ + default?: B; +}; + +type CellConfig = T extends { base?: infer D; quant?: infer Q } + ? NonNullable | NonNullable + : never; +type ConfigOf = Extract< + { [K in keyof V]: CellConfig }[keyof V], + { modelName: string } +>; +type BackendsOf = Extract; + +const BACKEND_ORDER: Backend[] = ['xnnpack', 'coreml', 'vulkan', 'qnn']; + +function firstBackend(variants: AnyVariantMap): Backend { + for (const b of BACKEND_ORDER) { + if (variants[b]) return b; + } + throw new Error('Model variant map is empty.'); +} + +function resolveBackend( + variants: AnyVariantMap, + platformDefaults: PlatformDefaults | undefined, + requested: Backend | undefined +): Backend { + if (requested) return requested; + if (platformDefaults) { + if (Platform.OS === 'ios' && platformDefaults.ios) + return platformDefaults.ios; + if (Platform.OS === 'android' && platformDefaults.android) { + return platformDefaults.android; + } + if (platformDefaults.default) return platformDefaults.default; + } + // Implicit platform default: prefer CoreML on iOS, XNNPACK on Android + // whenever the model ships that backend. Models can override via + // `platformDefaults`. + if (Platform.OS === 'ios' && variants.coreml) return 'coreml'; + if (Platform.OS === 'android' && variants.xnnpack) return 'xnnpack'; + return firstBackend(variants); +} + +function resolveCell(cell: BackendCell, quant: boolean): { modelName: string } { + // Fall back to the other slot when the requested precision is missing, + // so single-precision backends still work either way. + const primary = quant ? cell.quant : cell.base; + const fallback = quant ? cell.base : cell.quant; + const result = primary ?? fallback; + if (!result) { + throw new Error('Model variant cell has no config.'); + } + return result; +} + +function resolveVariant( + variants: AnyVariantMap, + platformDefaults: PlatformDefaults | undefined, + opts: ModelOpts +): { modelName: string } { + const backend = resolveBackend(variants, platformDefaults, opts.backend); + const cell = variants[backend]; + if (!cell) { + throw new Error(`Backend '${backend}' is not available for this model.`); + } + return resolveCell(cell, opts.quant !== false); +} + +// Build an Accessor from a per-backend variant map and an optional +// platform-default policy. The resulting accessor's `backend` parameter is +// typed to exactly the keys present in `variants`. +function variant( + variants: V, + platformDefaults?: PlatformDefaults> +): Accessor, BackendsOf> { + type C = ConfigOf; + type B = BackendsOf; + return (opts: ModelOpts = {}) => + resolveVariant(variants, platformDefaults, opts) as C; +} + +// Single-config accessor (xnnpack-only, no quantized variant). +function base(c: C) { + return variant({ xnnpack: { base: c } }); +} + +// xnnpack-only accessor with a `base` / `quant` pair. +function pair( + baseC: D, + quantC: Q +) { + return variant({ xnnpack: { base: baseC, quant: quantC } }); +} + +// TTS presets bundle model + voice + phonemizer in a single config; they +// don't share the `{ modelName: string }` shape of the rest of the registry, +// and have no quant/backend axis. Expose them as a plain `() => Config` +// accessor so the call style stays consistent (`models.text_to_speech.en_us.heart()`). +function tts(c: C): () => C { + return () => c; +} + +// ───────────────────────────────────────────────────────────────────────────── +// Per-backend variant maps for models that ship more than one backend. +// ───────────────────────────────────────────────────────────────────────────── + +const EFFICIENTNET_V2_S_VARIANTS = { + xnnpack: { + base: { + modelName: 'efficientnet-v2-s' as const, + modelSource: M.EFFICIENTNET_V2_S_XNNPACK_FP32_MODEL, + }, + quant: { + modelName: 'efficientnet-v2-s-quantized' as const, + modelSource: M.EFFICIENTNET_V2_S_XNNPACK_INT8_MODEL, + }, + }, + coreml: { + base: { + modelName: 'efficientnet-v2-s' as const, + modelSource: M.EFFICIENTNET_V2_S_COREML_FP32_MODEL, + }, + quant: { + modelName: 'efficientnet-v2-s-quantized' as const, + modelSource: M.EFFICIENTNET_V2_S_COREML_FP16_MODEL, + }, + }, +}; + +const SSDLITE_320_MOBILENET_V3_LARGE_VARIANTS = { + xnnpack: { + base: { + modelName: 'ssdlite-320-mobilenet-v3-large' as const, + modelSource: M.SSDLITE_320_MOBILENET_V3_LARGE_XNNPACK_FP32_MODEL, + }, + }, + coreml: { + base: { + modelName: 'ssdlite-320-mobilenet-v3-large' as const, + modelSource: M.SSDLITE_320_MOBILENET_V3_LARGE_COREML_FP16_MODEL, + }, + }, +}; + +const RF_DETR_NANO_VARIANTS = { + xnnpack: { + base: { + modelName: 'rf-detr-nano' as const, + modelSource: M.RF_DETR_NANO_XNNPACK_FP32_MODEL, + }, + }, + coreml: { + base: { + modelName: 'rf-detr-nano' as const, + modelSource: M.RF_DETR_NANO_COREML_INT8_MODEL, + }, + }, +}; + +const RF_DETR_NANO_SEG_VARIANTS = { + xnnpack: { + base: { + modelName: 'rfdetr-nano-seg' as const, + modelSource: M.RF_DETR_NANO_SEG_XNNPACK_FP32_MODEL, + }, + }, + coreml: { + base: { + modelName: 'rfdetr-nano-seg' as const, + modelSource: M.RF_DETR_NANO_SEG_COREML_INT8_MODEL, + }, + }, +}; + +const FASTSAM_S_VARIANTS = { + xnnpack: { + base: { + modelName: 'fastsam-s' as const, + modelSource: M.FASTSAM_S_XNNPACK_FP32_MODEL, + }, + }, + coreml: { + base: { + modelName: 'fastsam-s' as const, + modelSource: M.FASTSAM_S_COREML_FP16_MODEL, + }, + }, +}; + +const FASTSAM_X_VARIANTS = { + xnnpack: { + base: { + modelName: 'fastsam-x' as const, + modelSource: M.FASTSAM_X_XNNPACK_FP32_MODEL, + }, + }, + coreml: { + base: { + modelName: 'fastsam-x' as const, + modelSource: M.FASTSAM_X_COREML_FP16_MODEL, + }, + }, +}; + +function styleTransferVariants< + const Display extends string, + const Slug extends string, +>(display: Display, slug: Slug) { + const urls = M.styleTransferUrls(display, slug); + return { + xnnpack: { + base: { + modelName: `style-transfer-${display}`, + modelSource: urls.xnnpackBase, + } as { + modelName: `style-transfer-${Display}`; + modelSource: string; + }, + quant: { + modelName: `style-transfer-${display}-quantized`, + modelSource: urls.xnnpackQuant, + } as { + modelName: `style-transfer-${Display}-quantized`; + modelSource: string; + }, + }, + coreml: { + base: { + modelName: `style-transfer-${display}`, + modelSource: urls.coremlBase, + } as { + modelName: `style-transfer-${Display}`; + modelSource: string; + }, + quant: { + modelName: `style-transfer-${display}-quantized`, + modelSource: urls.coremlQuant, + } as { + modelName: `style-transfer-${Display}-quantized`; + modelSource: string; + }, + }, + }; +} + +const STYLE_TRANSFER_CANDY_VARIANTS = styleTransferVariants('candy', 'candy'); +const STYLE_TRANSFER_MOSAIC_VARIANTS = styleTransferVariants( + 'mosaic', + 'mosaic' +); +const STYLE_TRANSFER_RAIN_PRINCESS_VARIANTS = styleTransferVariants( + 'rain-princess', + 'rain_princess' +); +const STYLE_TRANSFER_UDNIE_VARIANTS = styleTransferVariants('udnie', 'udnie'); + +const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_VARIANTS = { + xnnpack: { + base: { + modelName: 'distiluse-base-multilingual-cased-v2-8da4w' as const, + modelSource: M.DISTILUSE_BASE_MULTILINGUAL_CASED_V2_8DA4W_MODEL, + tokenizerSource: M.DISTILUSE_BASE_MULTILINGUAL_CASED_V2_TOKENIZER, + }, + }, + coreml: { + base: { + modelName: 'distiluse-base-multilingual-cased-v2-coreml' as const, + modelSource: M.DISTILUSE_BASE_MULTILINGUAL_CASED_V2_COREML_MODEL, + tokenizerSource: M.DISTILUSE_BASE_MULTILINGUAL_CASED_V2_TOKENIZER, + }, + }, +}; + +// ───────────────────────────────────────────────────────────────────────────── +// OCR — language-parameterized accessor. +// +// The OCR pipeline ships one CRAFT detector + per-alphabet CRNN recognizers, +// already paired up in `OCR_` objects keyed by ISO language token +// (the `.language` field on each export). Build a runtime map from those +// exports so the user only needs to pass `{ language: 'en' }`. +// ───────────────────────────────────────────────────────────────────────────── + +type OcrConfig = typeof OCR.OCR_ABAZA; +type SupportedLanguage = keyof typeof symbols; + +const OCR_BY_LANGUAGE: Partial> = (() => { + const map: Partial> = {}; + for (const value of Object.values(OCR) as OcrConfig[]) { + if (value && typeof value === 'object' && 'language' in value) { + map[value.language as SupportedLanguage] = value; + } + } + return map; +})(); + +function craft({ language }: { language: SupportedLanguage }): OcrConfig { + const cfg = OCR_BY_LANGUAGE[language]; + if (!cfg) { + throw new Error( + `OCR is not published for language '${language}'. ` + + `Supported: ${Object.keys(OCR_BY_LANGUAGE).sort().join(', ')}` + ); + } + return cfg; +} + +/** + * Typed model registry grouped by capability. Each entry is a function-only + * accessor: call it (optionally with `{ quant, backend }`) to get the resolved + * config. The `backend` parameter is typed to exactly the backends a given + * model ships with — asking for a backend a model doesn't publish is a + * compile-time error. + * @example + * ```ts + * import { models } from 'react-native-executorch'; + * + * // Platform default (CoreML on iOS, XNNPACK on Android for multi-backend models). + * useObjectDetection({ model: models.object_detection.rf_detr_nano() }); + * + * // Explicit backend. + * useObjectDetection({ + * model: models.object_detection.rf_detr_nano({ backend: 'xnnpack' }), + * }); + * + * // Non-quantized variant. + * useLLM({ model: models.llm.llama3_2_3b({ quant: false }) }); + * + * // OCR — language-parameterized. + * useOcr({ model: models.ocr({ language: 'en' }) }); + * ``` + * @category Utils + */ +export const models = { + llm: { + llama3_2_1b: pair(M.LLAMA3_2_1B, M.LLAMA3_2_1B_SPINQUANT), + llama3_2_3b: pair(M.LLAMA3_2_3B, M.LLAMA3_2_3B_SPINQUANT), + qwen3_0_6b: pair(M.QWEN3_0_6B, M.QWEN3_0_6B_QUANTIZED), + qwen3_1_7b: pair(M.QWEN3_1_7B, M.QWEN3_1_7B_QUANTIZED), + qwen3_4b: pair(M.QWEN3_4B, M.QWEN3_4B_QUANTIZED), + qwen3_5_0_8b: base(M.QWEN3_5_0_8B_QUANTIZED), + qwen3_5_2b: base(M.QWEN3_5_2B_QUANTIZED), + qwen2_5_0_5b: pair(M.QWEN2_5_0_5B, M.QWEN2_5_0_5B_QUANTIZED), + qwen2_5_1_5b: pair(M.QWEN2_5_1_5B, M.QWEN2_5_1_5B_QUANTIZED), + qwen2_5_3b: pair(M.QWEN2_5_3B, M.QWEN2_5_3B_QUANTIZED), + hammer2_1_0_5b: pair(M.HAMMER2_1_0_5B, M.HAMMER2_1_0_5B_QUANTIZED), + hammer2_1_1_5b: pair(M.HAMMER2_1_1_5B, M.HAMMER2_1_1_5B_QUANTIZED), + hammer2_1_3b: pair(M.HAMMER2_1_3B, M.HAMMER2_1_3B_QUANTIZED), + smollm2_1_135m: pair(M.SMOLLM2_1_135M, M.SMOLLM2_1_135M_QUANTIZED), + smollm2_1_360m: pair(M.SMOLLM2_1_360M, M.SMOLLM2_1_360M_QUANTIZED), + smollm2_1_1_7b: pair(M.SMOLLM2_1_1_7B, M.SMOLLM2_1_1_7B_QUANTIZED), + phi_4_mini_4b: pair(M.PHI_4_MINI_4B, M.PHI_4_MINI_4B_QUANTIZED), + lfm2_5_350m: pair(M.LFM2_5_350M, M.LFM2_5_350M_QUANTIZED), + lfm2_5_1_2b_instruct: pair( + M.LFM2_5_1_2B_INSTRUCT, + M.LFM2_5_1_2B_INSTRUCT_QUANTIZED + ), + bielik_v3_0_1_5b: pair(M.BIELIK_V3_0_1_5B, M.BIELIK_V3_0_1_5B_QUANTIZED), + // Multimodal LLMs — same hook/module as plain LLMs, listed here so users + // pick a model by capability ("LLM") rather than by modality. + lfm2_5_vl_1_6b: base(M.LFM2_5_VL_1_6B_QUANTIZED), + lfm2_5_vl_450m: base(M.LFM2_5_VL_450M_QUANTIZED), + }, + classification: { + efficientnet_v2_s: variant(EFFICIENTNET_V2_S_VARIANTS), + }, + privacy_filter: { + openai: base(M.PRIVACY_FILTER_OPENAI), + nemotron: base(M.PRIVACY_FILTER_NEMOTRON), + }, + object_detection: { + ssdlite_320_mobilenet_v3_large: variant( + SSDLITE_320_MOBILENET_V3_LARGE_VARIANTS + ), + rf_detr_nano: variant(RF_DETR_NANO_VARIANTS), + yolo26n: base(M.YOLO26N), + yolo26s: base(M.YOLO26S), + yolo26m: base(M.YOLO26M), + yolo26l: base(M.YOLO26L), + yolo26x: base(M.YOLO26X), + fastsam_s: variant(FASTSAM_S_VARIANTS), + fastsam_x: variant(FASTSAM_X_VARIANTS), + }, + pose_estimation: { + yolo26n: base(M.YOLO26N_POSE), + }, + semantic_segmentation: { + deeplab_v3_resnet50: pair( + M.DEEPLAB_V3_RESNET50, + M.DEEPLAB_V3_RESNET50_QUANTIZED + ), + deeplab_v3_resnet101: pair( + M.DEEPLAB_V3_RESNET101, + M.DEEPLAB_V3_RESNET101_QUANTIZED + ), + deeplab_v3_mobilenet_v3_large: pair( + M.DEEPLAB_V3_MOBILENET_V3_LARGE, + M.DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED + ), + lraspp_mobilenet_v3_large: pair( + M.LRASPP_MOBILENET_V3_LARGE, + M.LRASPP_MOBILENET_V3_LARGE_QUANTIZED + ), + fcn_resnet50: pair(M.FCN_RESNET50, M.FCN_RESNET50_QUANTIZED), + fcn_resnet101: pair(M.FCN_RESNET101, M.FCN_RESNET101_QUANTIZED), + selfie_segmentation: base(M.SELFIE_SEGMENTATION), + }, + instance_segmentation: { + yolo26n_seg: base(M.YOLO26N_SEG), + yolo26s_seg: base(M.YOLO26S_SEG), + yolo26m_seg: base(M.YOLO26M_SEG), + yolo26l_seg: base(M.YOLO26L_SEG), + yolo26x_seg: base(M.YOLO26X_SEG), + rf_detr_nano_seg: variant(RF_DETR_NANO_SEG_VARIANTS), + }, + style_transfer: { + candy: variant(STYLE_TRANSFER_CANDY_VARIANTS), + mosaic: variant(STYLE_TRANSFER_MOSAIC_VARIANTS), + rain_princess: variant(STYLE_TRANSFER_RAIN_PRINCESS_VARIANTS), + udnie: variant(STYLE_TRANSFER_UDNIE_VARIANTS), + }, + speech_to_text: { + whisper_tiny_en: base(M.WHISPER_TINY_EN), + whisper_base_en: base(M.WHISPER_BASE_EN), + whisper_small_en: base(M.WHISPER_SMALL_EN), + whisper_tiny: base(M.WHISPER_TINY), + whisper_base: base(M.WHISPER_BASE), + whisper_small: base(M.WHISPER_SMALL), + }, + // Kokoro presets bundle model + voice + phonemizer per language. They go + // through `useTextToSpeech` directly — pick one and pass it as the `model`. + // Nested under the model family (`kokoro`) so a future TTS family can be + // added without breaking call sites. + text_to_speech: { + kokoro: { + en_us: { + heart: tts(KOKORO_AMERICAN_ENGLISH_FEMALE_HEART), + river: tts(KOKORO_AMERICAN_ENGLISH_FEMALE_RIVER), + sarah: tts(KOKORO_AMERICAN_ENGLISH_FEMALE_SARAH), + adam: tts(KOKORO_AMERICAN_ENGLISH_MALE_ADAM), + michael: tts(KOKORO_AMERICAN_ENGLISH_MALE_MICHAEL), + santa: tts(KOKORO_AMERICAN_ENGLISH_MALE_SANTA), + }, + en_gb: { + emma: tts(KOKORO_BRITISH_ENGLISH_FEMALE_EMMA), + daniel: tts(KOKORO_BRITISH_ENGLISH_MALE_DANIEL), + }, + fr: { + siwis: tts(KOKORO_FRENCH_FEMALE_SIWIS), + }, + es: { + dora: tts(KOKORO_SPANISH_FEMALE_DORA), + alex: tts(KOKORO_SPANISH_MALE_ALEX), + }, + it: { + sara: tts(KOKORO_ITALIAN_FEMALE_SARA), + nicola: tts(KOKORO_ITALIAN_MALE_NICOLA), + }, + pt: { + dora: tts(KOKORO_PORTUGUESE_FEMALE_DORA), + santa: tts(KOKORO_PORTUGUESE_MALE_SANTA), + }, + hi: { + alpha: tts(KOKORO_HINDI_FEMALE_ALPHA), + omega: tts(KOKORO_HINDI_MALE_OMEGA), + psi: tts(KOKORO_HINDI_MALE_PSI), + }, + pl: { + mateusz: tts(KOKORO_POLISH_MALE_MATEUSZ), + }, + de: { + anna: tts(KOKORO_GERMAN_FEMALE_ANNA), + }, + }, + }, + text_embedding: { + all_minilm_l6_v2: base(M.ALL_MINILM_L6_V2), + all_mpnet_base_v2: base(M.ALL_MPNET_BASE_V2), + multi_qa_minilm_l6_cos_v1: base(M.MULTI_QA_MINILM_L6_COS_V1), + multi_qa_mpnet_base_dot_v1: base(M.MULTI_QA_MPNET_BASE_DOT_V1), + distiluse_base_multilingual_cased_v2: variant( + DISTILUSE_BASE_MULTILINGUAL_CASED_V2_VARIANTS + ), + paraphrase_multilingual_minilm_l12_v2: base( + M.PARAPHRASE_MULTILINGUAL_MINILM_L12_V2_QUANTIZED + ), + clip_vit_base_patch32_text: base(M.CLIP_VIT_BASE_PATCH32_TEXT), + }, + image_embedding: { + clip_vit_base_patch32_image: pair( + M.CLIP_VIT_BASE_PATCH32_IMAGE, + M.CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED + ), + }, + image_generation: { + bk_sdm_tiny_vpred_512: base(M.BK_SDM_TINY_VPRED_512), + bk_sdm_tiny_vpred_256: base(M.BK_SDM_TINY_VPRED_256), + }, + vad: { + fsmn_vad: base(M.FSMN_VAD), + }, + // Nested under the detector model (`craft`) so a future OCR pipeline + // (e.g. an end-to-end TrOCR) can land as a sibling without breaking + // existing call sites. + ocr: { craft }, +} as const; diff --git a/packages/react-native-executorch/src/constants/modelUrls.ts b/packages/react-native-executorch/src/constants/modelUrls.ts index 159396add8..99d75f4626 100644 --- a/packages/react-native-executorch/src/constants/modelUrls.ts +++ b/packages/react-native-executorch/src/constants/modelUrls.ts @@ -3,19 +3,19 @@ import { PRIVACY_FILTER_NEMOTRON_LABELS, PRIVACY_FILTER_OPENAI_LABELS, } from './privacyFilterLabels'; -import { URL_PREFIX, PREVIOUS_VERSION_TAG, VERSION_TAG } from './versions'; +import { URL_PREFIX, VERSION_TAG, PREVIOUS_VERSION_TAG } from './versions'; // LLMs // LLAMA 3.2 -const LLAMA3_2_3B_MODEL = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/llama-3.2-3B/original/llama3_2_3B_bf16.pte`; +const LLAMA3_2_3B_MODEL = `${URL_PREFIX}-llama-3.2/${VERSION_TAG}/3b/xnnpack/llama_3_2_3b_xnnpack_bf16.pte`; const LLAMA3_2_3B_QLORA_MODEL = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/llama-3.2-3B/QLoRA/llama3_2-3B_qat_lora.pte`; -const LLAMA3_2_3B_SPINQUANT_MODEL = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/llama-3.2-3B/spinquant/llama3_2_3B_spinquant.pte`; -const LLAMA3_2_1B_MODEL = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/llama-3.2-1B/original/llama3_2_bf16.pte`; +const LLAMA3_2_3B_SPINQUANT_MODEL = `${URL_PREFIX}-llama-3.2/${VERSION_TAG}/3b/xnnpack/llama_3_2_3b_xnnpack_spinquant.pte`; +const LLAMA3_2_1B_MODEL = `${URL_PREFIX}-llama-3.2/${VERSION_TAG}/1b/xnnpack/llama_3_2_1b_xnnpack_bf16.pte`; const LLAMA3_2_1B_QLORA_MODEL = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/llama-3.2-1B/QLoRA/llama3_2_qat_lora.pte`; -const LLAMA3_2_1B_SPINQUANT_MODEL = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/llama-3.2-1B/spinquant/llama3_2_spinquant.pte`; -const LLAMA3_2_TOKENIZER = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const LLAMA3_2_TOKENIZER_CONFIG = `${URL_PREFIX}-llama-3.2/${PREVIOUS_VERSION_TAG}/tokenizer_config.json`; +const LLAMA3_2_1B_SPINQUANT_MODEL = `${URL_PREFIX}-llama-3.2/${VERSION_TAG}/1b/xnnpack/llama_3_2_1b_xnnpack_spinquant.pte`; +const LLAMA3_2_TOKENIZER = `${URL_PREFIX}-llama-3.2/${VERSION_TAG}/tokenizer.json`; +const LLAMA3_2_TOKENIZER_CONFIG = `${URL_PREFIX}-llama-3.2/${VERSION_TAG}/tokenizer_config.json`; /** * @category Models - LLM @@ -28,6 +28,10 @@ export const LLAMA3_2_3B = { } as const; /** + * @deprecated Use `LLAMA3_2_3B_SPINQUANT` instead — SpinQuant is the + * canonical quantized Llama 3.2 3B variant going forward. This alias + * still resolves the v0.8.0 file for back-compat and will be removed in + * a future major release. * @category Models - LLM */ export const LLAMA3_2_3B_QLORA = { @@ -58,6 +62,10 @@ export const LLAMA3_2_1B = { } as const; /** + * @deprecated Use `LLAMA3_2_1B_SPINQUANT` instead — SpinQuant is the + * canonical quantized Llama 3.2 1B variant going forward. This alias + * still resolves the v0.8.0 file for back-compat and will be removed in + * a future major release. * @category Models - LLM */ export const LLAMA3_2_1B_QLORA = { @@ -78,14 +86,14 @@ export const LLAMA3_2_1B_SPINQUANT = { } as const; // QWEN 3 -const QWEN3_0_6B_MODEL = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/qwen-3-0.6B/original/qwen3_0_6b_bf16.pte`; -const QWEN3_0_6B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/qwen-3-0.6B/quantized/qwen3_0_6b_8da4w.pte`; -const QWEN3_1_7B_MODEL = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/qwen-3-1.7B/original/qwen3_1_7b_bf16.pte`; -const QWEN3_1_7B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/qwen-3-1.7B/quantized/qwen3_1_7b_8da4w.pte`; -const QWEN3_4B_MODEL = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/qwen-3-4B/original/qwen3_4b_bf16.pte`; -const QWEN3_4B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/qwen-3-4B/quantized/qwen3_4b_8da4w.pte`; -const QWEN3_TOKENIZER = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const QWEN3_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-3/${PREVIOUS_VERSION_TAG}/tokenizer_config.json`; +const QWEN3_0_6B_MODEL = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/0_6b/xnnpack/qwen_3_0_6b_xnnpack_bf16.pte`; +const QWEN3_0_6B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/0_6b/xnnpack/qwen_3_0_6b_xnnpack_8da4w.pte`; +const QWEN3_1_7B_MODEL = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/1_7b/xnnpack/qwen_3_1_7b_xnnpack_bf16.pte`; +const QWEN3_1_7B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/1_7b/xnnpack/qwen_3_1_7b_xnnpack_8da4w.pte`; +const QWEN3_4B_MODEL = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/4b/xnnpack/qwen_3_4b_xnnpack_bf16.pte`; +const QWEN3_4B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/4b/xnnpack/qwen_3_4b_xnnpack_8da4w.pte`; +const QWEN3_TOKENIZER = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/tokenizer.json`; +const QWEN3_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-3/${VERSION_TAG}/tokenizer_config.json`; // Qwen3's published generation_config.json recommends temperature=0.6 and // top_p=0.95. We propagate those to every Qwen3 preset so model quality is @@ -162,14 +170,14 @@ export const QWEN3_4B_QUANTIZED = { } as const; // HAMMER 2.1 -const HAMMER2_1_0_5B_MODEL = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/hammer-2.1-0.5B/original/hammer2_1_0_5B_bf16.pte`; -const HAMMER2_1_0_5B_QUANTIZED_MODEL = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/hammer-2.1-0.5B/quantized/hammer2_1_0_5B_8da4w.pte`; -const HAMMER2_1_1_5B_MODEL = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/hammer-2.1-1.5B/original/hammer2_1_1_5B_bf16.pte`; -const HAMMER2_1_1_5B_QUANTIZED_MODEL = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/hammer-2.1-1.5B/quantized/hammer2_1_1_5B_8da4w.pte`; -const HAMMER2_1_3B_MODEL = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/hammer-2.1-3B/original/hammer2_1_3B_bf16.pte`; -const HAMMER2_1_3B_QUANTIZED_MODEL = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/hammer-2.1-3B/quantized/hammer2_1_3B_8da4w.pte`; -const HAMMER2_1_TOKENIZER = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const HAMMER2_1_TOKENIZER_CONFIG = `${URL_PREFIX}-hammer-2.1/${PREVIOUS_VERSION_TAG}/tokenizer_config.json`; +const HAMMER2_1_0_5B_MODEL = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/0_5b/xnnpack/hammer_2_1_0_5b_xnnpack_bf16.pte`; +const HAMMER2_1_0_5B_QUANTIZED_MODEL = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/0_5b/xnnpack/hammer_2_1_0_5b_xnnpack_8da4w.pte`; +const HAMMER2_1_1_5B_MODEL = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/1_5b/xnnpack/hammer_2_1_1_5b_xnnpack_bf16.pte`; +const HAMMER2_1_1_5B_QUANTIZED_MODEL = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/1_5b/xnnpack/hammer_2_1_1_5b_xnnpack_8da4w.pte`; +const HAMMER2_1_3B_MODEL = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/3b/xnnpack/hammer_2_1_3b_xnnpack_bf16.pte`; +const HAMMER2_1_3B_QUANTIZED_MODEL = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/3b/xnnpack/hammer_2_1_3b_xnnpack_8da4w.pte`; +const HAMMER2_1_TOKENIZER = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/tokenizer.json`; +const HAMMER2_1_TOKENIZER_CONFIG = `${URL_PREFIX}-hammer-2.1/${VERSION_TAG}/tokenizer_config.json`; /** * @category Models - LLM @@ -232,14 +240,14 @@ export const HAMMER2_1_3B_QUANTIZED = { } as const; // SMOLLM2 -const SMOLLM2_1_135M_MODEL = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/smolLm-2-135M/original/smolLm2_135M_bf16.pte`; -const SMOLLM2_1_135M_QUANTIZED_MODEL = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/smolLm-2-135M/quantized/smolLm2_135M_8da4w.pte`; -const SMOLLM2_1_360M_MODEL = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/smolLm-2-360M/original/smolLm2_360M_bf16.pte`; -const SMOLLM2_1_360M_QUANTIZED_MODEL = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/smolLm-2-360M/quantized/smolLm2_360M_8da4w.pte`; -const SMOLLM2_1_1_7B_MODEL = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/smolLm-2-1.7B/original/smolLm2_1_7B_bf16.pte`; -const SMOLLM2_1_1_7B_QUANTIZED_MODEL = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/smolLm-2-1.7B/quantized/smolLm2_1_7B_8da4w.pte`; -const SMOLLM2_1_TOKENIZER = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const SMOLLM2_1_TOKENIZER_CONFIG = `${URL_PREFIX}-smolLm-2/${PREVIOUS_VERSION_TAG}/tokenizer_config.json`; +const SMOLLM2_1_135M_MODEL = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/135m/xnnpack/smollm2_135m_xnnpack_bf16.pte`; +const SMOLLM2_1_135M_QUANTIZED_MODEL = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/135m/xnnpack/smollm2_135m_xnnpack_8da4w.pte`; +const SMOLLM2_1_360M_MODEL = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/360m/xnnpack/smollm2_360m_xnnpack_bf16.pte`; +const SMOLLM2_1_360M_QUANTIZED_MODEL = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/360m/xnnpack/smollm2_360m_xnnpack_8da4w.pte`; +const SMOLLM2_1_1_7B_MODEL = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/1_7b/xnnpack/smollm2_1_7b_xnnpack_bf16.pte`; +const SMOLLM2_1_1_7B_QUANTIZED_MODEL = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/1_7b/xnnpack/smollm2_1_7b_xnnpack_8da4w.pte`; +const SMOLLM2_1_TOKENIZER = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/tokenizer.json`; +const SMOLLM2_1_TOKENIZER_CONFIG = `${URL_PREFIX}-smolLm-2/${VERSION_TAG}/tokenizer_config.json`; /** * @category Models - LLM @@ -302,14 +310,14 @@ export const SMOLLM2_1_1_7B_QUANTIZED = { } as const; // QWEN 2.5 -const QWEN2_5_0_5B_MODEL = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/qwen-2.5-0.5B/original/qwen2_5_0_5b_bf16.pte`; -const QWEN2_5_0_5B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/qwen-2.5-0.5B/quantized/qwen2_5_0_5b_8da4w.pte`; -const QWEN2_5_1_5B_MODEL = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/qwen-2.5-1.5B/original/qwen2_5_1_5b_bf16.pte`; -const QWEN2_5_1_5B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/qwen-2.5-1.5B/quantized/qwen2_5_1_5b_8da4w.pte`; -const QWEN2_5_3B_MODEL = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/qwen-2.5-3B/original/qwen2_5_3b_bf16.pte`; -const QWEN2_5_3B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/qwen-2.5-3B/quantized/qwen2_5_3b_8da4w.pte`; -const QWEN2_5_TOKENIZER = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const QWEN2_5_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-2.5/${PREVIOUS_VERSION_TAG}/tokenizer_config.json`; +const QWEN2_5_0_5B_MODEL = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/0_5b/xnnpack/qwen_2_5_0_5b_xnnpack_bf16.pte`; +const QWEN2_5_0_5B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/0_5b/xnnpack/qwen_2_5_0_5b_xnnpack_8da4w.pte`; +const QWEN2_5_1_5B_MODEL = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/1_5b/xnnpack/qwen_2_5_1_5b_xnnpack_bf16.pte`; +const QWEN2_5_1_5B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/1_5b/xnnpack/qwen_2_5_1_5b_xnnpack_8da4w.pte`; +const QWEN2_5_3B_MODEL = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/3b/xnnpack/qwen_2_5_3b_xnnpack_bf16.pte`; +const QWEN2_5_3B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/3b/xnnpack/qwen_2_5_3b_xnnpack_8da4w.pte`; +const QWEN2_5_TOKENIZER = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/tokenizer.json`; +const QWEN2_5_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-2.5/${VERSION_TAG}/tokenizer_config.json`; /** * @category Models - LLM @@ -372,9 +380,9 @@ export const QWEN2_5_3B_QUANTIZED = { } as const; // QWEN3.5-0.8B -const QWEN3_5_0_8B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/Qwen3.5-0.8B/qwen3_5_0_8b_xnnpack_8da4w.pte`; -const QWEN3_5_0_8B_TOKENIZER = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/Qwen3.5-0.8B/tokenizer.json`; -const QWEN3_5_0_8B_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/Qwen3.5-0.8B/tokenizer_config.json`; +const QWEN3_5_0_8B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/0_8b/xnnpack/qwen_3_5_0_8b_xnnpack_8da4w.pte`; +const QWEN3_5_0_8B_TOKENIZER = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/0_8b/tokenizer.json`; +const QWEN3_5_0_8B_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/0_8b/tokenizer_config.json`; /** * @category Models - LLM @@ -387,9 +395,9 @@ export const QWEN3_5_0_8B_QUANTIZED = { } as const; // QWEN3.5-2B -const QWEN3_5_2B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/Qwen3.5-2B/qwen3_5_2b_xnnpack_8da4w.pte`; -const QWEN3_5_2B_TOKENIZER = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/Qwen3.5-2B/tokenizer.json`; -const QWEN3_5_2B_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/Qwen3.5-2B/tokenizer_config.json`; +const QWEN3_5_2B_QUANTIZED_MODEL = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/2b/xnnpack/qwen_3_5_2b_xnnpack_8da4w.pte`; +const QWEN3_5_2B_TOKENIZER = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/2b/tokenizer.json`; +const QWEN3_5_2B_TOKENIZER_CONFIG = `${URL_PREFIX}-qwen-3.5/${VERSION_TAG}/2b/tokenizer_config.json`; /** * @category Models - LLM @@ -402,10 +410,10 @@ export const QWEN3_5_2B_QUANTIZED = { } as const; // PHI 4 -const PHI_4_MINI_4B_MODEL = `${URL_PREFIX}-phi-4-mini/${PREVIOUS_VERSION_TAG}/original/phi-4-mini_bf16.pte`; -const PHI_4_MINI_4B_QUANTIZED_MODEL = `${URL_PREFIX}-phi-4-mini/${PREVIOUS_VERSION_TAG}/quantized/phi-4-mini_8da4w.pte`; -const PHI_4_MINI_TOKENIZER = `${URL_PREFIX}-phi-4-mini/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const PHI_4_MINI_TOKENIZER_CONFIG = `${URL_PREFIX}-phi-4-mini/${PREVIOUS_VERSION_TAG}/tokenizer_config.json`; +const PHI_4_MINI_4B_MODEL = `${URL_PREFIX}-phi-4-mini/${VERSION_TAG}/xnnpack/phi_4_mini_xnnpack_bf16.pte`; +const PHI_4_MINI_4B_QUANTIZED_MODEL = `${URL_PREFIX}-phi-4-mini/${VERSION_TAG}/xnnpack/phi_4_mini_xnnpack_8da4w.pte`; +const PHI_4_MINI_TOKENIZER = `${URL_PREFIX}-phi-4-mini/${VERSION_TAG}/tokenizer.json`; +const PHI_4_MINI_TOKENIZER_CONFIG = `${URL_PREFIX}-phi-4-mini/${VERSION_TAG}/tokenizer_config.json`; /** * @category Models - LLM @@ -428,10 +436,10 @@ export const PHI_4_MINI_4B_QUANTIZED = { } as const; // LFM2.5-1.2B-Instruct -const LFM2_5_1_2B_INSTRUCT_MODEL = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-1.2B-instruct/original/lfm2_5_1_2b_fp16.pte`; -const LFM2_5_1_2B_INSTRUCT_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-1.2B-instruct/quantized/lfm2_5_1_2b_8da4w.pte`; -const LFM2_5_1_2B_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-1.2B-instruct/tokenizer.json`; -const LFM2_5_1_2B_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-1.2B-instruct/tokenizer_config.json`; +const LFM2_5_1_2B_INSTRUCT_MODEL = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/1_2b/xnnpack/lfm_2_5_1_2b_xnnpack_fp16.pte`; +const LFM2_5_1_2B_INSTRUCT_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/1_2b/xnnpack/lfm_2_5_1_2b_xnnpack_8da4w.pte`; +const LFM2_5_1_2B_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/1_2b/tokenizer.json`; +const LFM2_5_1_2B_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/1_2b/tokenizer_config.json`; /** * @category Models - LLM @@ -454,10 +462,10 @@ export const LFM2_5_1_2B_INSTRUCT_QUANTIZED = { } as const; // LFM2.5-350M -const LFM2_5_350M_MODEL = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-350M/xnnpack/lfm2_5_350m_xnnpack_fp16.pte`; -const LFM2_5_350M_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-350M/xnnpack/lfm2_5_350m_xnnpack_8w4da.pte`; -const LFM2_5_350M_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-350M/tokenizer.json`; -const LFM2_5_350M_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-350M/tokenizer_config.json`; +const LFM2_5_350M_MODEL = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/350m/xnnpack/lfm_2_5_350m_xnnpack_fp16.pte`; +const LFM2_5_350M_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/350m/xnnpack/lfm_2_5_350m_xnnpack_8da4w.pte`; +const LFM2_5_350M_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/350m/tokenizer.json`; +const LFM2_5_350M_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/350m/tokenizer_config.json`; /** * @category Models - LLM @@ -480,10 +488,10 @@ export const LFM2_5_350M_QUANTIZED = { } as const; // Bielik-v3.0 -const BIELIK_V3_0_1_5B_MODEL = `${URL_PREFIX}-bielik-v3.0/${PREVIOUS_VERSION_TAG}/bielik-v3.0-1.5B/original/bielik_1_5b_v3_0_instruct_xnnpack_fp16.pte`; -const BIELIK_V3_0_1_5B_QUANTIZED_MODEL = `${URL_PREFIX}-bielik-v3.0/${PREVIOUS_VERSION_TAG}/bielik-v3.0-1.5B/quantized/bielik_1_5b_v3_0_instruct_xnnpack_8da4w.pte`; -const BIELIK_V3_0_TOKENIZER = `${URL_PREFIX}-bielik-v3.0/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const BIELIK_V3_0_TOKENIZER_CONFIG = `${URL_PREFIX}-bielik-v3.0/${PREVIOUS_VERSION_TAG}/tokenizer_config.json`; +const BIELIK_V3_0_1_5B_MODEL = `${URL_PREFIX}-bielik-v3.0/${VERSION_TAG}/xnnpack/bielik_v3_0_1_5b_xnnpack_fp16.pte`; +const BIELIK_V3_0_1_5B_QUANTIZED_MODEL = `${URL_PREFIX}-bielik-v3.0/${VERSION_TAG}/xnnpack/bielik_v3_0_1_5b_xnnpack_8da4w.pte`; +const BIELIK_V3_0_TOKENIZER = `${URL_PREFIX}-bielik-v3.0/${VERSION_TAG}/tokenizer.json`; +const BIELIK_V3_0_TOKENIZER_CONFIG = `${URL_PREFIX}-bielik-v3.0/${VERSION_TAG}/tokenizer_config.json`; /** * @category Models - LLM @@ -506,14 +514,14 @@ export const BIELIK_V3_0_1_5B_QUANTIZED = { } as const; // LFM2.5-VL-1.6B -const LFM2_VL_1_6B_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-VL-1.6B/quantized/lfm2_5_vl_1_6b_8da4w_xnnpack.pte`; -const LFM2_VL_1_6B_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-VL-1.6B/tokenizer.json`; -const LFM2_VL_1_6B_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-VL-1.6B/tokenizer_config.json`; +const LFM2_VL_1_6B_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/vl_1_6b/xnnpack/lfm_2_5_vl_1_6b_xnnpack_8da4w.pte`; +const LFM2_VL_1_6B_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/vl_1_6b/tokenizer.json`; +const LFM2_VL_1_6B_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/vl_1_6b/tokenizer_config.json`; // LFM2.5-VL-450M -const LFM2_VL_450M_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-VL-450M/lfm2_5_vl_450m_8da4w_xnnpack.pte`; -const LFM2_VL_450M_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-VL-450M/tokenizer.json`; -const LFM2_VL_450M_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${PREVIOUS_VERSION_TAG}/lfm2.5-VL-450M/tokenizer_config.json`; +const LFM2_VL_450M_QUANTIZED_MODEL = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/vl_450m/xnnpack/lfm_2_5_vl_450m_xnnpack_8da4w.pte`; +const LFM2_VL_450M_TOKENIZER = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/vl_450m/tokenizer.json`; +const LFM2_VL_450M_TOKENIZER_CONFIG = `${URL_PREFIX}-lfm-2.5/${VERSION_TAG}/vl_450m/tokenizer_config.json`; /** * @category Models - VLM @@ -565,14 +573,18 @@ export const LFM2_VL_1_6B_QUANTIZED = LFM2_5_VL_1_6B_QUANTIZED; export const LFM2_VL_450M_QUANTIZED = LFM2_5_VL_450M_QUANTIZED; // Classification +export const EFFICIENTNET_V2_S_XNNPACK_FP32_MODEL = `${URL_PREFIX}-efficientnet-v2-s/${VERSION_TAG}/xnnpack/efficientnet_v2_s_xnnpack_fp32.pte`; +export const EFFICIENTNET_V2_S_XNNPACK_INT8_MODEL = `${URL_PREFIX}-efficientnet-v2-s/${VERSION_TAG}/xnnpack/efficientnet_v2_s_xnnpack_int8.pte`; +export const EFFICIENTNET_V2_S_COREML_FP32_MODEL = `${URL_PREFIX}-efficientnet-v2-s/${VERSION_TAG}/coreml/efficientnet_v2_s_coreml_fp32.pte`; +export const EFFICIENTNET_V2_S_COREML_FP16_MODEL = `${URL_PREFIX}-efficientnet-v2-s/${VERSION_TAG}/coreml/efficientnet_v2_s_coreml_fp16.pte`; const EFFICIENTNET_V2_S_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-efficientnet-v2-s/${PREVIOUS_VERSION_TAG}/coreml/efficientnet_v2_s_coreml_fp32.pte` - : `${URL_PREFIX}-efficientnet-v2-s/${PREVIOUS_VERSION_TAG}/xnnpack/efficientnet_v2_s_xnnpack_fp32.pte`; + ? EFFICIENTNET_V2_S_COREML_FP32_MODEL + : EFFICIENTNET_V2_S_XNNPACK_FP32_MODEL; const EFFICIENTNET_V2_S_QUANTIZED_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-efficientnet-v2-s/${PREVIOUS_VERSION_TAG}/coreml/efficientnet_v2_s_coreml_fp16.pte` - : `${URL_PREFIX}-efficientnet-v2-s/${PREVIOUS_VERSION_TAG}/xnnpack/efficientnet_v2_s_xnnpack_int8.pte`; + ? EFFICIENTNET_V2_S_COREML_FP16_MODEL + : EFFICIENTNET_V2_S_XNNPACK_INT8_MODEL; /** * @category Models - Classification @@ -591,14 +603,18 @@ export const EFFICIENTNET_V2_S_QUANTIZED = { } as const; // Object detection +export const SSDLITE_320_MOBILENET_V3_LARGE_XNNPACK_FP32_MODEL = `${URL_PREFIX}-ssdlite320-mobilenet-v3-large/${VERSION_TAG}/xnnpack/ssdlite320_mobilenet_v3_large_xnnpack_fp32.pte`; +export const SSDLITE_320_MOBILENET_V3_LARGE_COREML_FP16_MODEL = `${URL_PREFIX}-ssdlite320-mobilenet-v3-large/${VERSION_TAG}/coreml/ssdlite320_mobilenet_v3_large_coreml_fp16.pte`; +export const RF_DETR_NANO_XNNPACK_FP32_MODEL = `${URL_PREFIX}-rfdetr-nano-detector/${VERSION_TAG}/xnnpack/rfdetr_nano_xnnpack_fp32.pte`; +export const RF_DETR_NANO_COREML_INT8_MODEL = `${URL_PREFIX}-rfdetr-nano-detector/${VERSION_TAG}/coreml/rfdetr_nano_coreml_int8.pte`; const SSDLITE_320_MOBILENET_V3_LARGE_MODEL = Platform.OS === 'ios' - ? `${URL_PREFIX}-ssdlite320-mobilenet-v3-large/${PREVIOUS_VERSION_TAG}/coreml/ssdlite320_mobilenet_v3_large_coreml_fp16.pte` - : `${URL_PREFIX}-ssdlite320-mobilenet-v3-large/${PREVIOUS_VERSION_TAG}/xnnpack/ssdlite320_mobilenet_v3_large_xnnpack_fp32.pte`; + ? SSDLITE_320_MOBILENET_V3_LARGE_COREML_FP16_MODEL + : SSDLITE_320_MOBILENET_V3_LARGE_XNNPACK_FP32_MODEL; const RF_DETR_NANO_MODEL = Platform.OS === 'ios' - ? `${URL_PREFIX}-rfdetr-nano-detector/${PREVIOUS_VERSION_TAG}/coreml/rfdetr_n_det_coreml_int8.pte` - : `${URL_PREFIX}-rfdetr-nano-detector/${PREVIOUS_VERSION_TAG}/rfdetr_detector.pte`; + ? RF_DETR_NANO_COREML_INT8_MODEL + : RF_DETR_NANO_XNNPACK_FP32_MODEL; /** * @category Models - Object Detection @@ -617,11 +633,11 @@ export const RF_DETR_NANO = { } as const; // YOLO26 Object Detection -const YOLO26N_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${PREVIOUS_VERSION_TAG}/yolo26n/xnnpack/yolo26n.pte`; -const YOLO26S_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${PREVIOUS_VERSION_TAG}/yolo26s/xnnpack/yolo26s.pte`; -const YOLO26M_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${PREVIOUS_VERSION_TAG}/yolo26m/xnnpack/yolo26m.pte`; -const YOLO26L_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${PREVIOUS_VERSION_TAG}/yolo26l/xnnpack/yolo26l.pte`; -const YOLO26X_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${PREVIOUS_VERSION_TAG}/yolo26x/xnnpack/yolo26x.pte`; +const YOLO26N_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${VERSION_TAG}/n/xnnpack/yolo26_n_xnnpack_fp32.pte`; +const YOLO26S_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${VERSION_TAG}/s/xnnpack/yolo26_s_xnnpack_fp32.pte`; +const YOLO26M_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${VERSION_TAG}/m/xnnpack/yolo26_m_xnnpack_fp32.pte`; +const YOLO26L_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${VERSION_TAG}/l/xnnpack/yolo26_l_xnnpack_fp32.pte`; +const YOLO26X_DETECTION_MODEL = `${URL_PREFIX}-yolo26/${VERSION_TAG}/x/xnnpack/yolo26_x_xnnpack_fp32.pte`; /** * @category Models - Object Detection @@ -664,7 +680,7 @@ export const YOLO26X = { } as const; // YOLO26 Pose Estimation -const YOLO26N_POSE_MODEL = `${URL_PREFIX}-yolo26-pose/${VERSION_TAG}/yolo26n/xnnpack/yolo26n-pose_xnnpack.pte`; +const YOLO26N_POSE_MODEL = `${URL_PREFIX}-yolo26-pose/${VERSION_TAG}/xnnpack/yolo26_pose_n_xnnpack_fp32.pte`; /** * @category Models - Pose Estimation @@ -675,38 +691,63 @@ export const YOLO26N_POSE = { } as const; // Style transfer +/** + * Builds the four `(backend, precision)` URLs for a single style-transfer style. + * @param display - HF repo suffix (e.g. `rain-princess`). + * @param slug - .pte filename token (e.g. `rain_princess`). Differs from + * `display` for styles whose names contain spaces. + * @returns Per-(backend, precision) URLs for the requested style. + */ +export function styleTransferUrls< + const Display extends string, + const Slug extends string, +>(display: Display, slug: Slug) { + return { + xnnpackBase: `${URL_PREFIX}-style-transfer-${display}/${VERSION_TAG}/xnnpack/style_transfer_${slug}_xnnpack_fp32.pte`, + xnnpackQuant: `${URL_PREFIX}-style-transfer-${display}/${VERSION_TAG}/xnnpack/style_transfer_${slug}_xnnpack_int8.pte`, + coremlBase: `${URL_PREFIX}-style-transfer-${display}/${VERSION_TAG}/coreml/style_transfer_${slug}_coreml_fp32.pte`, + coremlQuant: `${URL_PREFIX}-style-transfer-${display}/${VERSION_TAG}/coreml/style_transfer_${slug}_coreml_fp16.pte`, + }; +} +const STYLE_TRANSFER_CANDY_URLS = styleTransferUrls('candy', 'candy'); +const STYLE_TRANSFER_MOSAIC_URLS = styleTransferUrls('mosaic', 'mosaic'); +const STYLE_TRANSFER_RAIN_PRINCESS_URLS = styleTransferUrls( + 'rain-princess', + 'rain_princess' +); +const STYLE_TRANSFER_UDNIE_URLS = styleTransferUrls('udnie', 'udnie'); const STYLE_TRANSFER_CANDY_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-candy/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_candy_coreml_fp32.pte` - : `${URL_PREFIX}-style-transfer-candy/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_candy_xnnpack_fp32.pte`; + ? STYLE_TRANSFER_CANDY_URLS.coremlBase + : STYLE_TRANSFER_CANDY_URLS.xnnpackBase; const STYLE_TRANSFER_CANDY_QUANTIZED_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-candy/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_candy_coreml_fp16.pte` - : `${URL_PREFIX}-style-transfer-candy/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_candy_xnnpack_int8.pte`; + ? STYLE_TRANSFER_CANDY_URLS.coremlQuant + : STYLE_TRANSFER_CANDY_URLS.xnnpackQuant; const STYLE_TRANSFER_MOSAIC_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-mosaic/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_mosaic_coreml_fp32.pte` - : `${URL_PREFIX}-style-transfer-mosaic/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_mosaic_xnnpack_fp32.pte`; + ? STYLE_TRANSFER_MOSAIC_URLS.coremlBase + : STYLE_TRANSFER_MOSAIC_URLS.xnnpackBase; const STYLE_TRANSFER_MOSAIC_QUANTIZED_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-mosaic/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_mosaic_coreml_fp16.pte` - : `${URL_PREFIX}-style-transfer-mosaic/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_mosaic_xnnpack_int8.pte`; + ? STYLE_TRANSFER_MOSAIC_URLS.coremlQuant + : STYLE_TRANSFER_MOSAIC_URLS.xnnpackQuant; const STYLE_TRANSFER_RAIN_PRINCESS_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-rain-princess/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_rain_princess_coreml_fp32.pte` - : `${URL_PREFIX}-style-transfer-rain-princess/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_rain_princess_xnnpack_fp32.pte`; + ? STYLE_TRANSFER_RAIN_PRINCESS_URLS.coremlBase + : STYLE_TRANSFER_RAIN_PRINCESS_URLS.xnnpackBase; const STYLE_TRANSFER_RAIN_PRINCESS_QUANTIZED_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-rain-princess/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_rain_princess_coreml_fp16.pte` - : `${URL_PREFIX}-style-transfer-rain-princess/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_rain_princess_xnnpack_int8.pte`; + ? STYLE_TRANSFER_RAIN_PRINCESS_URLS.coremlQuant + : STYLE_TRANSFER_RAIN_PRINCESS_URLS.xnnpackQuant; const STYLE_TRANSFER_UDNIE_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-udnie/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_udnie_coreml_fp32.pte` - : `${URL_PREFIX}-style-transfer-udnie/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_udnie_xnnpack_fp32.pte`; + ? STYLE_TRANSFER_UDNIE_URLS.coremlBase + : STYLE_TRANSFER_UDNIE_URLS.xnnpackBase; const STYLE_TRANSFER_UDNIE_QUANTIZED_MODEL = Platform.OS === `ios` - ? `${URL_PREFIX}-style-transfer-udnie/${PREVIOUS_VERSION_TAG}/coreml/style_transfer_udnie_coreml_fp16.pte` - : `${URL_PREFIX}-style-transfer-udnie/${PREVIOUS_VERSION_TAG}/xnnpack/style_transfer_udnie_xnnpack_int8.pte`; + ? STYLE_TRANSFER_UDNIE_URLS.coremlQuant + : STYLE_TRANSFER_UDNIE_URLS.xnnpackQuant; /** * @category Models - Style Transfer @@ -773,32 +814,32 @@ export const STYLE_TRANSFER_UDNIE_QUANTIZED = { } as const; // S2T -const WHISPER_TINY_EN_TOKENIZER = `${URL_PREFIX}-whisper-tiny.en/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_TINY_EN_MODEL = `${URL_PREFIX}-whisper-tiny.en/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_tiny_en_xnnpack.pte`; +const WHISPER_TINY_EN_TOKENIZER = `${URL_PREFIX}-whisper-tiny.en/${VERSION_TAG}/tokenizer.json`; +const WHISPER_TINY_EN_MODEL = `${URL_PREFIX}-whisper-tiny.en/${VERSION_TAG}/xnnpack/whisper_tiny_en_xnnpack_fp32.pte`; -const WHISPER_TINY_EN_QUANTIZED_TOKENIZER = `${URL_PREFIX}-whisper-tiny-quantized.en/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_TINY_EN_QUANTIZED_MODEL = `${URL_PREFIX}-whisper-tiny-quantized.en/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_tiny_en_quantized_xnnpack.pte`; +const WHISPER_TINY_EN_QUANTIZED_TOKENIZER = `${URL_PREFIX}-whisper-tiny.en/${VERSION_TAG}/tokenizer.json`; +const WHISPER_TINY_EN_QUANTIZED_MODEL = `${URL_PREFIX}-whisper-tiny.en/${VERSION_TAG}/xnnpack/whisper_tiny_en_xnnpack_int8.pte`; -const WHISPER_BASE_EN_TOKENIZER = `${URL_PREFIX}-whisper-base.en/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_BASE_EN_MODEL = `${URL_PREFIX}-whisper-base.en/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_base_en_xnnpack.pte`; +const WHISPER_BASE_EN_TOKENIZER = `${URL_PREFIX}-whisper-base.en/${VERSION_TAG}/tokenizer.json`; +const WHISPER_BASE_EN_MODEL = `${URL_PREFIX}-whisper-base.en/${VERSION_TAG}/xnnpack/whisper_base_en_xnnpack_fp32.pte`; -const WHISPER_BASE_EN_QUANTIZED_TOKENIZER = `${URL_PREFIX}-whisper-base-quantized.en/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_BASE_EN_QUANTIZED_MODEL = `${URL_PREFIX}-whisper-base-quantized.en/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_base_en_quantized_xnnpack.pte`; +const WHISPER_BASE_EN_QUANTIZED_TOKENIZER = `${URL_PREFIX}-whisper-base.en/${VERSION_TAG}/tokenizer.json`; +const WHISPER_BASE_EN_QUANTIZED_MODEL = `${URL_PREFIX}-whisper-base.en/${VERSION_TAG}/xnnpack/whisper_base_en_xnnpack_int8.pte`; -const WHISPER_SMALL_EN_TOKENIZER = `${URL_PREFIX}-whisper-small.en/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_SMALL_EN_MODEL = `${URL_PREFIX}-whisper-small.en/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_small_en_xnnpack.pte`; +const WHISPER_SMALL_EN_TOKENIZER = `${URL_PREFIX}-whisper-small.en/${VERSION_TAG}/tokenizer.json`; +const WHISPER_SMALL_EN_MODEL = `${URL_PREFIX}-whisper-small.en/${VERSION_TAG}/xnnpack/whisper_small_en_xnnpack_fp32.pte`; -const WHISPER_SMALL_EN_QUANTIZED_TOKENIZER = `${URL_PREFIX}-whisper-small-quantized.en/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_SMALL_EN_QUANTIZED_MODEL = `${URL_PREFIX}-whisper-small-quantized.en/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_small_en_quantized_xnnpack.pte`; +const WHISPER_SMALL_EN_QUANTIZED_TOKENIZER = `${URL_PREFIX}-whisper-small.en/${VERSION_TAG}/tokenizer.json`; +const WHISPER_SMALL_EN_QUANTIZED_MODEL = `${URL_PREFIX}-whisper-small.en/${VERSION_TAG}/xnnpack/whisper_small_en_xnnpack_int8.pte`; -const WHISPER_TINY_TOKENIZER = `${URL_PREFIX}-whisper-tiny/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_TINY_MODEL = `${URL_PREFIX}-whisper-tiny/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_tiny_xnnpack.pte`; +const WHISPER_TINY_TOKENIZER = `${URL_PREFIX}-whisper-tiny/${VERSION_TAG}/tokenizer.json`; +const WHISPER_TINY_MODEL = `${URL_PREFIX}-whisper-tiny/${VERSION_TAG}/xnnpack/whisper_tiny_xnnpack_fp32.pte`; -const WHISPER_BASE_TOKENIZER = `${URL_PREFIX}-whisper-base/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_BASE_MODEL = `${URL_PREFIX}-whisper-base/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_base_xnnpack.pte`; +const WHISPER_BASE_TOKENIZER = `${URL_PREFIX}-whisper-base/${VERSION_TAG}/tokenizer.json`; +const WHISPER_BASE_MODEL = `${URL_PREFIX}-whisper-base/${VERSION_TAG}/xnnpack/whisper_base_xnnpack_fp32.pte`; -const WHISPER_SMALL_TOKENIZER = `${URL_PREFIX}-whisper-small/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const WHISPER_SMALL_MODEL = `${URL_PREFIX}-whisper-small/${PREVIOUS_VERSION_TAG}/xnnpack/whisper_small_xnnpack.pte`; +const WHISPER_SMALL_TOKENIZER = `${URL_PREFIX}-whisper-small/${VERSION_TAG}/tokenizer.json`; +const WHISPER_SMALL_MODEL = `${URL_PREFIX}-whisper-small/${VERSION_TAG}/xnnpack/whisper_small_xnnpack_fp32.pte`; /** * @category Models - Speech To Text @@ -891,18 +932,18 @@ export const WHISPER_SMALL = { } as const; // Semantic Segmentation -const DEEPLAB_V3_RESNET50_MODEL = `${URL_PREFIX}-deeplab-v3/${PREVIOUS_VERSION_TAG}/deeplab-v3-resnet50/xnnpack/deeplabv3_resnet50_xnnpack_fp32.pte`; -const DEEPLAB_V3_RESNET101_MODEL = `${URL_PREFIX}-deeplab-v3/${PREVIOUS_VERSION_TAG}/deeplab-v3-resnet101/xnnpack/deeplabv3_resnet101_xnnpack_fp32.pte`; -const DEEPLAB_V3_MOBILENET_V3_LARGE_MODEL = `${URL_PREFIX}-deeplab-v3/${PREVIOUS_VERSION_TAG}/deeplab-v3-mobilenet-v3-large/xnnpack/deeplabv3_mobilenet_v3_large_xnnpack_fp32.pte`; -const LRASPP_MOBILENET_V3_LARGE_MODEL = `${URL_PREFIX}-lraspp/${PREVIOUS_VERSION_TAG}/xnnpack/lraspp_mobilenet_v3_large_xnnpack_fp32.pte`; -const FCN_RESNET50_MODEL = `${URL_PREFIX}-fcn/${PREVIOUS_VERSION_TAG}/fcn-resnet50/xnnpack/fcn_resnet50_xnnpack_fp32.pte`; -const FCN_RESNET101_MODEL = `${URL_PREFIX}-fcn/${PREVIOUS_VERSION_TAG}/fcn-resnet101/xnnpack/fcn_resnet101_xnnpack_fp32.pte`; -const DEEPLAB_V3_RESNET50_QUANTIZED_MODEL = `${URL_PREFIX}-deeplab-v3/${PREVIOUS_VERSION_TAG}/deeplab-v3-resnet50/xnnpack/deeplabv3_resnet50_xnnpack_int8.pte`; -const DEEPLAB_V3_RESNET101_QUANTIZED_MODEL = `${URL_PREFIX}-deeplab-v3/${PREVIOUS_VERSION_TAG}/deeplab-v3-resnet101/xnnpack/deeplabv3_resnet101_xnnpack_int8.pte`; -const DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED_MODEL = `${URL_PREFIX}-deeplab-v3/${PREVIOUS_VERSION_TAG}/deeplab-v3-mobilenet-v3-large/xnnpack/deeplabv3_mobilenet_v3_large_xnnpack_int8.pte`; -const LRASPP_MOBILENET_V3_LARGE_QUANTIZED_MODEL = `${URL_PREFIX}-lraspp/${PREVIOUS_VERSION_TAG}/xnnpack/lraspp_mobilenet_v3_large_xnnpack_int8.pte`; -const FCN_RESNET50_QUANTIZED_MODEL = `${URL_PREFIX}-fcn/${PREVIOUS_VERSION_TAG}/fcn-resnet50/xnnpack/fcn_resnet50_xnnpack_int8.pte`; -const FCN_RESNET101_QUANTIZED_MODEL = `${URL_PREFIX}-fcn/${PREVIOUS_VERSION_TAG}/fcn-resnet101/xnnpack/fcn_resnet101_xnnpack_int8.pte`; +const DEEPLAB_V3_RESNET50_MODEL = `${URL_PREFIX}-deeplab-v3/${VERSION_TAG}/xnnpack/deeplab_v3_resnet50_xnnpack_fp32.pte`; +const DEEPLAB_V3_RESNET101_MODEL = `${URL_PREFIX}-deeplab-v3/${VERSION_TAG}/xnnpack/deeplab_v3_resnet101_xnnpack_fp32.pte`; +const DEEPLAB_V3_MOBILENET_V3_LARGE_MODEL = `${URL_PREFIX}-deeplab-v3/${VERSION_TAG}/xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_fp32.pte`; +const LRASPP_MOBILENET_V3_LARGE_MODEL = `${URL_PREFIX}-lraspp/${VERSION_TAG}/xnnpack/lraspp_mobilenet_v3_large_xnnpack_fp32.pte`; +const FCN_RESNET50_MODEL = `${URL_PREFIX}-fcn/${VERSION_TAG}/xnnpack/fcn_resnet50_xnnpack_fp32.pte`; +const FCN_RESNET101_MODEL = `${URL_PREFIX}-fcn/${VERSION_TAG}/xnnpack/fcn_resnet101_xnnpack_fp32.pte`; +const DEEPLAB_V3_RESNET50_QUANTIZED_MODEL = `${URL_PREFIX}-deeplab-v3/${VERSION_TAG}/xnnpack/deeplab_v3_resnet50_xnnpack_int8.pte`; +const DEEPLAB_V3_RESNET101_QUANTIZED_MODEL = `${URL_PREFIX}-deeplab-v3/${VERSION_TAG}/xnnpack/deeplab_v3_resnet101_xnnpack_int8.pte`; +const DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED_MODEL = `${URL_PREFIX}-deeplab-v3/${VERSION_TAG}/xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_int8.pte`; +const LRASPP_MOBILENET_V3_LARGE_QUANTIZED_MODEL = `${URL_PREFIX}-lraspp/${VERSION_TAG}/xnnpack/lraspp_mobilenet_v3_large_xnnpack_int8.pte`; +const FCN_RESNET50_QUANTIZED_MODEL = `${URL_PREFIX}-fcn/${VERSION_TAG}/xnnpack/fcn_resnet50_xnnpack_int8.pte`; +const FCN_RESNET101_QUANTIZED_MODEL = `${URL_PREFIX}-fcn/${VERSION_TAG}/xnnpack/fcn_resnet101_xnnpack_int8.pte`; /** * @category Models - Semantic Segmentation @@ -1000,7 +1041,7 @@ export const FCN_RESNET101_QUANTIZED = { modelSource: FCN_RESNET101_QUANTIZED_MODEL, } as const; -const SELFIE_SEGMENTATION_MODEL = `${URL_PREFIX}-selfie-segmentation/${PREVIOUS_VERSION_TAG}/xnnpack/selfie-segmentation.pte`; +const SELFIE_SEGMENTATION_MODEL = `${URL_PREFIX}-selfie-segmentation/${VERSION_TAG}/xnnpack/selfie_segmentation_xnnpack_fp32.pte`; /** * @category Models - Semantic Segmentation @@ -1011,14 +1052,18 @@ export const SELFIE_SEGMENTATION = { } as const; // FastSAM Instance Segmentation +export const FASTSAM_S_XNNPACK_FP32_MODEL = `${URL_PREFIX}-fast-sam/${VERSION_TAG}/s/xnnpack/fast_sam_s_xnnpack_fp32.pte`; +export const FASTSAM_S_COREML_FP16_MODEL = `${URL_PREFIX}-fast-sam/${VERSION_TAG}/s/coreml/fast_sam_s_coreml_fp16.pte`; +export const FASTSAM_X_XNNPACK_FP32_MODEL = `${URL_PREFIX}-fast-sam/${VERSION_TAG}/x/xnnpack/fast_sam_x_xnnpack_fp32.pte`; +export const FASTSAM_X_COREML_FP16_MODEL = `${URL_PREFIX}-fast-sam/${VERSION_TAG}/x/coreml/fast_sam_x_coreml_fp16.pte`; const FASTSAM_S_SEG_MODEL = Platform.OS === 'ios' - ? `${URL_PREFIX}-fast-sam/${VERSION_TAG}/fastsam-s/coreml/fastsam_s_coreml_fp16.pte` - : `${URL_PREFIX}-fast-sam/${VERSION_TAG}/fastsam-s/xnnpack/fastsam_s_xnnpack_fp32.pte`; + ? FASTSAM_S_COREML_FP16_MODEL + : FASTSAM_S_XNNPACK_FP32_MODEL; const FASTSAM_X_SEG_MODEL = Platform.OS === 'ios' - ? `${URL_PREFIX}-fast-sam/${VERSION_TAG}/fastsam-x/coreml/fastsam_x_coreml_fp16.pte` - : `${URL_PREFIX}-fast-sam/${VERSION_TAG}/fastsam-x/xnnpack/fastsam_x_xnnpack_fp32.pte`; + ? FASTSAM_X_COREML_FP16_MODEL + : FASTSAM_X_XNNPACK_FP32_MODEL; /** * @category Models - Instance Segmentation @@ -1039,15 +1084,17 @@ export const FASTSAM_X = { /** * @category Models - Instance Segmentation */ -const YOLO26N_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${PREVIOUS_VERSION_TAG}/yolo26n-seg/xnnpack/yolo26n-seg.pte`; -const YOLO26S_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${PREVIOUS_VERSION_TAG}/yolo26s-seg/xnnpack/yolo26s-seg.pte`; -const YOLO26M_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${PREVIOUS_VERSION_TAG}/yolo26m-seg/xnnpack/yolo26m-seg.pte`; -const YOLO26L_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${PREVIOUS_VERSION_TAG}/yolo26l-seg/xnnpack/yolo26l-seg.pte`; -const YOLO26X_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${PREVIOUS_VERSION_TAG}/yolo26x-seg/xnnpack/yolo26x-seg.pte`; +const YOLO26N_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${VERSION_TAG}/n/xnnpack/yolo26_seg_n_xnnpack_fp32.pte`; +const YOLO26S_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${VERSION_TAG}/s/xnnpack/yolo26_seg_s_xnnpack_fp32.pte`; +const YOLO26M_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${VERSION_TAG}/m/xnnpack/yolo26_seg_m_xnnpack_fp32.pte`; +const YOLO26L_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${VERSION_TAG}/l/xnnpack/yolo26_seg_l_xnnpack_fp32.pte`; +const YOLO26X_SEG_MODEL = `${URL_PREFIX}-yolo26-seg/${VERSION_TAG}/x/xnnpack/yolo26_seg_x_xnnpack_fp32.pte`; +export const RF_DETR_NANO_SEG_XNNPACK_FP32_MODEL = `${URL_PREFIX}-rfdetr-nano-segmentation/${VERSION_TAG}/xnnpack/rfdetr_nano_xnnpack_fp32.pte`; +export const RF_DETR_NANO_SEG_COREML_INT8_MODEL = `${URL_PREFIX}-rfdetr-nano-segmentation/${VERSION_TAG}/coreml/rfdetr_nano_coreml_int8.pte`; const RF_DETR_NANO_SEG_MODEL = Platform.OS === 'ios' - ? `${URL_PREFIX}-rfdetr-nano-segmentation/${PREVIOUS_VERSION_TAG}/coreml/rfdetr_n_seg_coreml_int8.pte` - : `${URL_PREFIX}-rfdetr-nano-segmentation/${PREVIOUS_VERSION_TAG}/rfdetr_segmentation.pte`; + ? RF_DETR_NANO_SEG_COREML_INT8_MODEL + : RF_DETR_NANO_SEG_XNNPACK_FP32_MODEL; /** * @category Models - Instance Segmentation */ @@ -1097,8 +1144,8 @@ export const RF_DETR_NANO_SEG = { } as const; // Image Embeddings -const CLIP_VIT_BASE_PATCH32_IMAGE_MODEL = `${URL_PREFIX}-clip-vit-base-patch32/${PREVIOUS_VERSION_TAG}/xnnpack/clip_vit_base_patch32_vision_xnnpack_fp32.pte`; -const CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED_MODEL = `${URL_PREFIX}-clip-vit-base-patch32/${PREVIOUS_VERSION_TAG}/xnnpack/clip_vit_base_patch32_vision_xnnpack_int8.pte`; +const CLIP_VIT_BASE_PATCH32_IMAGE_MODEL = `${URL_PREFIX}-clip-vit-base-patch32/${VERSION_TAG}/xnnpack/clip_vit_base_patch32_image_xnnpack_fp32.pte`; +const CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED_MODEL = `${URL_PREFIX}-clip-vit-base-patch32/${VERSION_TAG}/xnnpack/clip_vit_base_patch32_image_xnnpack_int8.pte`; /** * @category Models - Image Embeddings @@ -1117,21 +1164,21 @@ export const CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED = { } as const; // Text Embeddings -const ALL_MINILM_L6_V2_MODEL = `${URL_PREFIX}-all-MiniLM-L6-v2/${PREVIOUS_VERSION_TAG}/all-MiniLM-L6-v2_xnnpack.pte`; -const ALL_MINILM_L6_V2_TOKENIZER = `${URL_PREFIX}-all-MiniLM-L6-v2/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const ALL_MPNET_BASE_V2_MODEL = `${URL_PREFIX}-all-mpnet-base-v2/${PREVIOUS_VERSION_TAG}/all-mpnet-base-v2_xnnpack.pte`; -const ALL_MPNET_BASE_V2_TOKENIZER = `${URL_PREFIX}-all-mpnet-base-v2/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const MULTI_QA_MINILM_L6_COS_V1_MODEL = `${URL_PREFIX}-multi-qa-MiniLM-L6-cos-v1/${PREVIOUS_VERSION_TAG}/multi-qa-MiniLM-L6-cos-v1_xnnpack.pte`; -const MULTI_QA_MINILM_L6_COS_V1_TOKENIZER = `${URL_PREFIX}-multi-qa-MiniLM-L6-cos-v1/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const MULTI_QA_MPNET_BASE_DOT_V1_MODEL = `${URL_PREFIX}-multi-qa-mpnet-base-dot-v1/${PREVIOUS_VERSION_TAG}/multi-qa-mpnet-base-dot-v1_xnnpack.pte`; -const MULTI_QA_MPNET_BASE_DOT_V1_TOKENIZER = `${URL_PREFIX}-multi-qa-mpnet-base-dot-v1/${PREVIOUS_VERSION_TAG}/tokenizer.json`; -const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_8DA4W_MODEL = `${URL_PREFIX}-distiluse-base-multilingual-cased-v2/${VERSION_TAG}/xnnpack/distiluse-base-multilingual-cased-v2_xnnpack_8da4w.pte`; -const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_COREML_MODEL = `${URL_PREFIX}-distiluse-base-multilingual-cased-v2/${VERSION_TAG}/coreml/distiluse-base-multilingual-cased-v2_coreml_fp32.pte`; -const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_TOKENIZER = `${URL_PREFIX}-distiluse-base-multilingual-cased-v2/${VERSION_TAG}/tokenizer.json`; -const PARAPHRASE_MULTILINGUAL_MINILM_L12_V2_QUANTIZED_MODEL = `${URL_PREFIX}-paraphrase-multilingual-MiniLM-L12-v2/${VERSION_TAG}/xnnpack/paraphrase-multilingual-MiniLM-L12-v2_xnnpack_8da4w.pte`; +const ALL_MINILM_L6_V2_MODEL = `${URL_PREFIX}-all-MiniLM-L6-v2/${VERSION_TAG}/xnnpack/all_minilm_l6_v2_xnnpack_fp32.pte`; +const ALL_MINILM_L6_V2_TOKENIZER = `${URL_PREFIX}-all-MiniLM-L6-v2/${VERSION_TAG}/tokenizer.json`; +const ALL_MPNET_BASE_V2_MODEL = `${URL_PREFIX}-all-mpnet-base-v2/${VERSION_TAG}/xnnpack/all_mpnet_base_v2_xnnpack_fp32.pte`; +const ALL_MPNET_BASE_V2_TOKENIZER = `${URL_PREFIX}-all-mpnet-base-v2/${VERSION_TAG}/tokenizer.json`; +const MULTI_QA_MINILM_L6_COS_V1_MODEL = `${URL_PREFIX}-multi-qa-MiniLM-L6-cos-v1/${VERSION_TAG}/xnnpack/multi_qa_minilm_l6_cos_v1_xnnpack_fp32.pte`; +const MULTI_QA_MINILM_L6_COS_V1_TOKENIZER = `${URL_PREFIX}-multi-qa-MiniLM-L6-cos-v1/${VERSION_TAG}/tokenizer.json`; +const MULTI_QA_MPNET_BASE_DOT_V1_MODEL = `${URL_PREFIX}-multi-qa-mpnet-base-dot-v1/${VERSION_TAG}/xnnpack/multi_qa_mpnet_base_dot_v1_xnnpack_fp32.pte`; +const MULTI_QA_MPNET_BASE_DOT_V1_TOKENIZER = `${URL_PREFIX}-multi-qa-mpnet-base-dot-v1/${VERSION_TAG}/tokenizer.json`; +export const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_8DA4W_MODEL = `${URL_PREFIX}-distiluse-base-multilingual-cased-v2/${VERSION_TAG}/xnnpack/distiluse_base_multilingual_cased_v2_xnnpack_8da4w.pte`; +export const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_COREML_MODEL = `${URL_PREFIX}-distiluse-base-multilingual-cased-v2/${VERSION_TAG}/coreml/distiluse_base_multilingual_cased_v2_coreml_fp32.pte`; +export const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_TOKENIZER = `${URL_PREFIX}-distiluse-base-multilingual-cased-v2/${VERSION_TAG}/tokenizer.json`; +const PARAPHRASE_MULTILINGUAL_MINILM_L12_V2_QUANTIZED_MODEL = `${URL_PREFIX}-paraphrase-multilingual-MiniLM-L12-v2/${VERSION_TAG}/xnnpack/paraphrase_multilingual_minilm_l12_v2_xnnpack_8da4w.pte`; const PARAPHRASE_MULTILINGUAL_MINILM_L12_V2_TOKENIZER = `${URL_PREFIX}-paraphrase-multilingual-MiniLM-L12-v2/${VERSION_TAG}/tokenizer.json`; -const CLIP_VIT_BASE_PATCH32_TEXT_MODEL = `${URL_PREFIX}-clip-vit-base-patch32/${PREVIOUS_VERSION_TAG}/xnnpack/clip_vit_base_patch32_text_xnnpack_fp32.pte`; -const CLIP_VIT_BASE_PATCH32_TEXT_TOKENIZER = `${URL_PREFIX}-clip-vit-base-patch32/${PREVIOUS_VERSION_TAG}/tokenizer.json`; +const CLIP_VIT_BASE_PATCH32_TEXT_MODEL = `${URL_PREFIX}-clip-vit-base-patch32/${VERSION_TAG}/xnnpack/clip_vit_base_patch32_text_xnnpack_fp32.pte`; +const CLIP_VIT_BASE_PATCH32_TEXT_TOKENIZER = `${URL_PREFIX}-clip-vit-base-patch32/${VERSION_TAG}/tokenizer.json`; /** * @category Models - Text Embeddings @@ -1171,6 +1218,8 @@ export const MULTI_QA_MPNET_BASE_DOT_V1 = { /** * @category Models - Text Embeddings + * @deprecated Use `MODEL_REGISTRY.TEXT_EMBEDDING.DISTILUSE_BASE_MULTILINGUAL_CASED_V2` + * (defaults to xnnpack on Android) or pass `{ backend: 'xnnpack' }`. */ export const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_8DA4W = { modelName: 'distiluse-base-multilingual-cased-v2-8da4w', @@ -1180,6 +1229,7 @@ export const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_8DA4W = { /** * @category Models - Text Embeddings + * @deprecated Use `MODEL_REGISTRY.TEXT_EMBEDDING.DISTILUSE_BASE_MULTILINGUAL_CASED_V2({ backend: 'coreml' })`. */ export const DISTILUSE_BASE_MULTILINGUAL_CASED_V2_COREML = { modelName: 'distiluse-base-multilingual-cased-v2-coreml', @@ -1220,7 +1270,7 @@ export const CLIP_VIT_BASE_PATCH32_TEXT = { */ export const PRIVACY_FILTER_OPENAI = { modelName: 'privacy-filter-openai', - modelSource: `${URL_PREFIX}-privacy-filter-openai/${VERSION_TAG}/xnnpack/privacy-filter_xnnpack_8da4w.pte`, + modelSource: `${URL_PREFIX}-privacy-filter-openai/${VERSION_TAG}/xnnpack/privacy_filter_openai_xnnpack_8da4w.pte`, tokenizerSource: `${URL_PREFIX}-privacy-filter-openai/${VERSION_TAG}/tokenizer.json`, labelNames: PRIVACY_FILTER_OPENAI_LABELS, } as const; @@ -1233,7 +1283,7 @@ export const PRIVACY_FILTER_OPENAI = { */ export const PRIVACY_FILTER_NEMOTRON = { modelName: 'privacy-filter-nemotron', - modelSource: `${URL_PREFIX}-privacy-filter-nemotron/${VERSION_TAG}/xnnpack/privacy-filter-nemotron_xnnpack_8da4w.pte`, + modelSource: `${URL_PREFIX}-privacy-filter-nemotron/${VERSION_TAG}/xnnpack/privacy_filter_nemotron_xnnpack_8da4w.pte`, tokenizerSource: `${URL_PREFIX}-privacy-filter-nemotron/${VERSION_TAG}/tokenizer.json`, labelNames: PRIVACY_FILTER_NEMOTRON_LABELS, } as const; @@ -1245,11 +1295,11 @@ export const PRIVACY_FILTER_NEMOTRON = { */ export const BK_SDM_TINY_VPRED_512 = { modelName: 'bk-sdm-tiny-vpred-512', - schedulerSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/scheduler/scheduler_config.json`, - tokenizerSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/tokenizer/tokenizer.json`, - encoderSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/text_encoder/model.pte`, - unetSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/unet/model.pte`, - decoderSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/vae/model.pte`, + schedulerSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/scheduler/scheduler_config.json`, + tokenizerSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/tokenizer/tokenizer.json`, + encoderSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/xnnpack/bk_sdm_tiny_text_encoder_xnnpack_fp32.pte`, + unetSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/xnnpack/bk_sdm_tiny_unet_xnnpack_fp32.pte`, + decoderSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/xnnpack/bk_sdm_tiny_vae_xnnpack_fp32.pte`, } as const; /** @@ -1257,15 +1307,15 @@ export const BK_SDM_TINY_VPRED_512 = { */ export const BK_SDM_TINY_VPRED_256 = { modelName: 'bk-sdm-tiny-vpred-256', - schedulerSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/scheduler/scheduler_config.json`, - tokenizerSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/tokenizer/tokenizer.json`, - encoderSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/text_encoder/model.pte`, - unetSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/unet/model.256.pte`, - decoderSource: `${URL_PREFIX}-bk-sdm-tiny/${PREVIOUS_VERSION_TAG}/vae/model.256.pte`, + schedulerSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/scheduler/scheduler_config.json`, + tokenizerSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/tokenizer/tokenizer.json`, + encoderSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/xnnpack/bk_sdm_tiny_text_encoder_xnnpack_fp32.pte`, + unetSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/xnnpack/bk_sdm_tiny_unet_256_xnnpack_fp32.pte`, + decoderSource: `${URL_PREFIX}-bk-sdm-tiny/${VERSION_TAG}/xnnpack/bk_sdm_tiny_vae_256_xnnpack_fp32.pte`, } as const; // Voice Activity Detection -const FSMN_VAD_MODEL = `${URL_PREFIX}-fsmn-vad/${PREVIOUS_VERSION_TAG}/xnnpack/fsmn-vad_xnnpack.pte`; +const FSMN_VAD_MODEL = `${URL_PREFIX}-fsmn-vad/${VERSION_TAG}/xnnpack/fsmn_vad_xnnpack_fp32.pte`; /** * @category Models - Voice Activity Detection @@ -1275,131 +1325,112 @@ export const FSMN_VAD = { modelSource: FSMN_VAD_MODEL, } as const; -/** - * Registry of all available model configurations. - * - * Use this to discover and enumerate all models shipped with the library. - * @example - * ```ts - * import { MODEL_REGISTRY } from 'react-native-executorch'; - * - * // List all model names - * const names = Object.values(MODEL_REGISTRY).map(m => m.modelName); - * - * // Find models by name substring - * const whisperModels = Object.values(MODEL_REGISTRY) - * .filter(m => m.modelName.includes('whisper')); - * ``` - * @category Utils - */ -export const MODEL_REGISTRY = { - ALL_MODELS: { - LLAMA3_2_3B, - LLAMA3_2_3B_QLORA, - LLAMA3_2_3B_SPINQUANT, - LLAMA3_2_1B, - LLAMA3_2_1B_QLORA, - LLAMA3_2_1B_SPINQUANT, - QWEN3_0_6B, - QWEN3_0_6B_QUANTIZED, - QWEN3_1_7B, - QWEN3_1_7B_QUANTIZED, - QWEN3_4B, - QWEN3_4B_QUANTIZED, - QWEN3_5_0_8B_QUANTIZED, - QWEN3_5_2B_QUANTIZED, - HAMMER2_1_0_5B, - HAMMER2_1_0_5B_QUANTIZED, - HAMMER2_1_1_5B, - HAMMER2_1_1_5B_QUANTIZED, - HAMMER2_1_3B, - HAMMER2_1_3B_QUANTIZED, - SMOLLM2_1_135M, - SMOLLM2_1_135M_QUANTIZED, - SMOLLM2_1_360M, - SMOLLM2_1_360M_QUANTIZED, - SMOLLM2_1_1_7B, - SMOLLM2_1_1_7B_QUANTIZED, - QWEN2_5_0_5B, - QWEN2_5_0_5B_QUANTIZED, - QWEN2_5_1_5B, - QWEN2_5_1_5B_QUANTIZED, - QWEN2_5_3B, - QWEN2_5_3B_QUANTIZED, - PHI_4_MINI_4B, - PHI_4_MINI_4B_QUANTIZED, - LFM2_5_350M, - LFM2_5_350M_QUANTIZED, - LFM2_5_1_2B_INSTRUCT, - LFM2_5_1_2B_INSTRUCT_QUANTIZED, - LFM2_5_VL_1_6B_QUANTIZED, - LFM2_5_VL_450M_QUANTIZED, - LFM2_VL_1_6B_QUANTIZED, - LFM2_VL_450M_QUANTIZED, - BIELIK_V3_0_1_5B, - BIELIK_V3_0_1_5B_QUANTIZED, - EFFICIENTNET_V2_S, - EFFICIENTNET_V2_S_QUANTIZED, - SSDLITE_320_MOBILENET_V3_LARGE, - RF_DETR_NANO, - STYLE_TRANSFER_CANDY, - STYLE_TRANSFER_CANDY_QUANTIZED, - STYLE_TRANSFER_MOSAIC, - STYLE_TRANSFER_MOSAIC_QUANTIZED, - STYLE_TRANSFER_RAIN_PRINCESS, - STYLE_TRANSFER_RAIN_PRINCESS_QUANTIZED, - STYLE_TRANSFER_UDNIE, - STYLE_TRANSFER_UDNIE_QUANTIZED, - WHISPER_TINY_EN, - WHISPER_TINY_EN_QUANTIZED, - WHISPER_BASE_EN, - WHISPER_BASE_EN_QUANTIZED, - WHISPER_SMALL_EN, - WHISPER_SMALL_EN_QUANTIZED, - WHISPER_TINY, - WHISPER_BASE, - WHISPER_SMALL, - DEEPLAB_V3_RESNET50, - DEEPLAB_V3_RESNET101, - DEEPLAB_V3_MOBILENET_V3_LARGE, - LRASPP_MOBILENET_V3_LARGE, - FCN_RESNET50, - FCN_RESNET101, - DEEPLAB_V3_RESNET50_QUANTIZED, - DEEPLAB_V3_RESNET101_QUANTIZED, - DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED, - LRASPP_MOBILENET_V3_LARGE_QUANTIZED, - FCN_RESNET50_QUANTIZED, - FCN_RESNET101_QUANTIZED, - SELFIE_SEGMENTATION, - YOLO26N_SEG, - YOLO26S_SEG, - YOLO26M_SEG, - YOLO26L_SEG, - YOLO26X_SEG, - RF_DETR_NANO_SEG, - FASTSAM_S, - FASTSAM_X, - CLIP_VIT_BASE_PATCH32_IMAGE, - CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED, - ALL_MINILM_L6_V2, - ALL_MPNET_BASE_V2, - MULTI_QA_MINILM_L6_COS_V1, - MULTI_QA_MPNET_BASE_DOT_V1, - DISTILUSE_BASE_MULTILINGUAL_CASED_V2_8DA4W, - DISTILUSE_BASE_MULTILINGUAL_CASED_V2_COREML, - PARAPHRASE_MULTILINGUAL_MINILM_L12_V2_QUANTIZED, - CLIP_VIT_BASE_PATCH32_TEXT, - BK_SDM_TINY_VPRED_512, - BK_SDM_TINY_VPRED_256, - FSMN_VAD, - PRIVACY_FILTER_OPENAI, - PRIVACY_FILTER_NEMOTRON, - }, -} as const; +// Internal — populates the urlToModelName lookup below. Not exported: the +// typed grouping lives in `./modelRegistry` as MODEL_REGISTRY. +const _ALL_MODELS = [ + LLAMA3_2_3B, + LLAMA3_2_3B_QLORA, + LLAMA3_2_3B_SPINQUANT, + LLAMA3_2_1B, + LLAMA3_2_1B_QLORA, + LLAMA3_2_1B_SPINQUANT, + QWEN3_0_6B, + QWEN3_0_6B_QUANTIZED, + QWEN3_1_7B, + QWEN3_1_7B_QUANTIZED, + QWEN3_4B, + QWEN3_4B_QUANTIZED, + QWEN3_5_0_8B_QUANTIZED, + QWEN3_5_2B_QUANTIZED, + HAMMER2_1_0_5B, + HAMMER2_1_0_5B_QUANTIZED, + HAMMER2_1_1_5B, + HAMMER2_1_1_5B_QUANTIZED, + HAMMER2_1_3B, + HAMMER2_1_3B_QUANTIZED, + SMOLLM2_1_135M, + SMOLLM2_1_135M_QUANTIZED, + SMOLLM2_1_360M, + SMOLLM2_1_360M_QUANTIZED, + SMOLLM2_1_1_7B, + SMOLLM2_1_1_7B_QUANTIZED, + QWEN2_5_0_5B, + QWEN2_5_0_5B_QUANTIZED, + QWEN2_5_1_5B, + QWEN2_5_1_5B_QUANTIZED, + QWEN2_5_3B, + QWEN2_5_3B_QUANTIZED, + PHI_4_MINI_4B, + PHI_4_MINI_4B_QUANTIZED, + LFM2_5_350M, + LFM2_5_350M_QUANTIZED, + LFM2_5_1_2B_INSTRUCT, + LFM2_5_1_2B_INSTRUCT_QUANTIZED, + LFM2_5_VL_1_6B_QUANTIZED, + LFM2_5_VL_450M_QUANTIZED, + BIELIK_V3_0_1_5B, + BIELIK_V3_0_1_5B_QUANTIZED, + EFFICIENTNET_V2_S, + EFFICIENTNET_V2_S_QUANTIZED, + SSDLITE_320_MOBILENET_V3_LARGE, + RF_DETR_NANO, + STYLE_TRANSFER_CANDY, + STYLE_TRANSFER_CANDY_QUANTIZED, + STYLE_TRANSFER_MOSAIC, + STYLE_TRANSFER_MOSAIC_QUANTIZED, + STYLE_TRANSFER_RAIN_PRINCESS, + STYLE_TRANSFER_RAIN_PRINCESS_QUANTIZED, + STYLE_TRANSFER_UDNIE, + STYLE_TRANSFER_UDNIE_QUANTIZED, + WHISPER_TINY_EN, + WHISPER_TINY_EN_QUANTIZED, + WHISPER_BASE_EN, + WHISPER_BASE_EN_QUANTIZED, + WHISPER_SMALL_EN, + WHISPER_SMALL_EN_QUANTIZED, + WHISPER_TINY, + WHISPER_BASE, + WHISPER_SMALL, + DEEPLAB_V3_RESNET50, + DEEPLAB_V3_RESNET101, + DEEPLAB_V3_MOBILENET_V3_LARGE, + LRASPP_MOBILENET_V3_LARGE, + FCN_RESNET50, + FCN_RESNET101, + DEEPLAB_V3_RESNET50_QUANTIZED, + DEEPLAB_V3_RESNET101_QUANTIZED, + DEEPLAB_V3_MOBILENET_V3_LARGE_QUANTIZED, + LRASPP_MOBILENET_V3_LARGE_QUANTIZED, + FCN_RESNET50_QUANTIZED, + FCN_RESNET101_QUANTIZED, + SELFIE_SEGMENTATION, + YOLO26N_SEG, + YOLO26S_SEG, + YOLO26M_SEG, + YOLO26L_SEG, + YOLO26X_SEG, + RF_DETR_NANO_SEG, + FASTSAM_S, + FASTSAM_X, + CLIP_VIT_BASE_PATCH32_IMAGE, + CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED, + ALL_MINILM_L6_V2, + ALL_MPNET_BASE_V2, + MULTI_QA_MINILM_L6_COS_V1, + MULTI_QA_MPNET_BASE_DOT_V1, + DISTILUSE_BASE_MULTILINGUAL_CASED_V2_8DA4W, + DISTILUSE_BASE_MULTILINGUAL_CASED_V2_COREML, + PARAPHRASE_MULTILINGUAL_MINILM_L12_V2_QUANTIZED, + CLIP_VIT_BASE_PATCH32_TEXT, + BK_SDM_TINY_VPRED_512, + BK_SDM_TINY_VPRED_256, + FSMN_VAD, + PRIVACY_FILTER_OPENAI, + PRIVACY_FILTER_NEMOTRON, +]; const urlToModelName = new Map(); -for (const config of Object.values(MODEL_REGISTRY.ALL_MODELS)) { +for (const config of _ALL_MODELS) { const modelName = config.modelName; for (const [key, value] of Object.entries(config)) { if (key !== 'modelName' && typeof value === 'string') { diff --git a/packages/react-native-executorch/src/constants/ocr/models.ts b/packages/react-native-executorch/src/constants/ocr/models.ts index 990156a8bd..b906f6f12b 100644 --- a/packages/react-native-executorch/src/constants/ocr/models.ts +++ b/packages/react-native-executorch/src/constants/ocr/models.ts @@ -1,11 +1,11 @@ import { alphabets, symbols } from './symbols'; -import { URL_PREFIX, PREVIOUS_VERSION_TAG } from '../versions'; +import { URL_PREFIX, VERSION_TAG } from '../versions'; -const DETECTOR_CRAFT_MODEL = `${URL_PREFIX}-detector-craft/${PREVIOUS_VERSION_TAG}/xnnpack_quantized/xnnpack_craft_quantized.pte`; +const DETECTOR_CRAFT_MODEL = `${URL_PREFIX}-detector-craft/${VERSION_TAG}/xnnpack/craft_xnnpack_int8.pte`; const createHFRecognizerDownloadUrl = (alphabet: keyof typeof alphabets) => - `${URL_PREFIX}-recognizer-crnn.en/${PREVIOUS_VERSION_TAG}/xnnpack/${alphabet}/xnnpack_crnn_${alphabet}.pte`; + `${URL_PREFIX}-recognizer-crnn.en/${VERSION_TAG}/${alphabet}/xnnpack/crnn_${alphabet}_xnnpack_fp32.pte`; const RECOGNIZER_ENGLISH_CRNN = createHFRecognizerDownloadUrl('english'); const RECOGNIZER_LATIN_CRNN = createHFRecognizerDownloadUrl('latin'); diff --git a/packages/react-native-executorch/src/constants/ocr/symbols.ts b/packages/react-native-executorch/src/constants/ocr/symbols.ts index e122958c6b..0947b2e8b7 100644 --- a/packages/react-native-executorch/src/constants/ocr/symbols.ts +++ b/packages/react-native-executorch/src/constants/ocr/symbols.ts @@ -8,7 +8,6 @@ export const alphabets = { ' !"#$%&\'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz{|}~ªÀÁÂÃÄÅÆÇÈÉÊËÌÍÎÏÐÑÒÓÔÕÖØÙÚÛÜÝÞßàáâãäåæçèéêëìíîïðñòóôõöøùúûüýþÿĀāĂ㥹ĆćČčĎďĐđĒēĖėĘęĚěĞğĨĩĪīĮįİıĶķĹĺĻļĽľŁłŃńŅņŇňŒœŔŕŘřŚśŞşŠšŤťŨũŪūŮůŲųŸŹźŻżŽžƏƠơƯưȘșȚțə̇ḌḍḶḷṀṁṂṃṄṅṆṇṬṭẠạẢảẤấẦầẨẩẪẫẬậẮắẰằẲẳẴẵẶặẸẹẺẻẼẽẾếỀềỂểỄễỆệỈỉỊịỌọỎỏỐốỒồỔổỖỗỘộỚớỜờỞởỠỡỢợỤụỦủỨứỪừỬửỮữỰựỲỳỴỵỶỷỸỹ€', japanese: ' 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- /* eslint-disable camelcase */ zh_sim: ' 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korean: diff --git a/packages/react-native-executorch/src/constants/versions.ts b/packages/react-native-executorch/src/constants/versions.ts index 9ce8a726d8..c272d992fe 100644 --- a/packages/react-native-executorch/src/constants/versions.ts +++ b/packages/react-native-executorch/src/constants/versions.ts @@ -2,5 +2,7 @@ export const LIB_VERSION = '0.9.0'; export const URL_PREFIX = 'https://huggingface.co/software-mansion/react-native-executorch'; +// Used by @deprecated constants that still resolve v0.8.0 files (e.g. the +// Llama QLoRA aliases superseded by SpinQuant). export const PREVIOUS_VERSION_TAG = 'resolve/v0.8.0'; export const VERSION_TAG = `resolve/v${LIB_VERSION}`; diff --git a/packages/react-native-executorch/src/controllers/LLMController.ts b/packages/react-native-executorch/src/controllers/LLMController.ts index 5eb8edaed0..dab1cc70ff 100644 --- a/packages/react-native-executorch/src/controllers/LLMController.ts +++ b/packages/react-native-executorch/src/controllers/LLMController.ts @@ -113,7 +113,10 @@ export class LLMController { const modelPath = modelResult?.[0]; if (!tokenizerPath || !tokenizerConfigPath || !modelPath) { - throw new RnExecutorchError(RnExecutorchErrorCode.DownloadInterrupted); + throw new RnExecutorchError( + RnExecutorchErrorCode.DownloadInterrupted, + 'The download has been interrupted. As a result, not every file was downloaded. Please retry the download.' + ); } this.tokenizerConfig = JSON.parse( @@ -257,7 +260,7 @@ export class LLMController { if (this._isGenerating) { throw new RnExecutorchError( RnExecutorchErrorCode.ModelGenerating, - 'You cannot delete the model now. You need to interrupt it first.' + 'You cannot delete the model now. You need ot interrupt it first.' ); } @@ -271,10 +274,16 @@ export class LLMController { public async forward(input: string, imagePaths?: string[]): Promise { if (!this._isReady) { - throw new RnExecutorchError(RnExecutorchErrorCode.ModuleNotLoaded); + throw new RnExecutorchError( + RnExecutorchErrorCode.ModuleNotLoaded, + 'The model is currently not loaded. Please load the model before calling forward().' + ); } if (this._isGenerating) { - throw new RnExecutorchError(RnExecutorchErrorCode.ModelGenerating); + throw new RnExecutorchError( + RnExecutorchErrorCode.ModelGenerating, + 'The model is currently generating. Please wait until previous model run is complete.' + ); } try { this.isGeneratingCallback(true); @@ -360,7 +369,6 @@ export class LLMController { messages, this.tokenizerConfig, tools, - // eslint-disable-next-line camelcase { tools_in_user_message: false, add_generation_prompt: true } ); @@ -389,7 +397,6 @@ export class LLMController { messages, this.tokenizerConfig, this.toolsConfig?.tools, - // eslint-disable-next-line camelcase { tools_in_user_message: false, add_generation_prompt: true } ); const textTokens = this.nativeModule.countTextTokens(rendered); diff --git a/packages/react-native-executorch/src/index.ts b/packages/react-native-executorch/src/index.ts index a33e9bdce0..556d35de02 100644 --- a/packages/react-native-executorch/src/index.ts +++ b/packages/react-native-executorch/src/index.ts @@ -239,6 +239,7 @@ export * from './types/poseEstimation'; export * from './constants/commonVision'; export * from './constants/classification'; export * from './constants/modelUrls'; +export * from './constants/modelRegistry'; export * from './constants/ocr/models'; export * from './constants/tts/models'; export * from './constants/tts/voices';