brainy/models/sentence-encoder/metadata.json

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**feat(models): add scripts for model compression, bundling, and optimization** - Added new scripts under `brainy-models-package/scripts`: - **`compress-models.js`**: Implements model compression with float16 and int8 precision to create optimized variants of Universal Sentence Encoder models. - **`download-full-models.js`**: Downloads the complete Universal Sentence Encoder model for offline usage. - **`download-model.js`**: Downloads reference files for TensorFlow Hub-based Universal Sentence Encoder. - Introduced a demonstration script: - **`demo-optional-model-bundling.js`**: Highlights the solution of bundling models to eliminate network dependency, ensuring reliability and offline capability. - Key Features: - **Compression**: - Reduced model size with float16 (balanced precision and size) and int8 (low-memory environments) options. - Generated compression summaries for quick insights into model variants and saved space. - **Offline Reliability**: - Bundled versions eliminate first-load delays, network dependencies, and failures. - Ensures rapid initialization in offline and memory-constrained scenarios. - **Dynamic Optimization**: - Tailored optimization profiles for various use cases: general, low-memory, and high-performance. - **Demonstration and Documentation**: - Comprehensive demo showcasing benefits of bundled models over online loading. - Examples for usage, testing, and integration with Brainy. **Purpose**: Introduce essential scripts and tools to enable efficient, offline-ready model usage, streamlining the embedding workflow while ensuring reliability in production and resource-constrained environments.
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{
"name": "universal-sentence-encoder",
"version": "1.0.0",
"description": "Universal Sentence Encoder model for text embeddings",
"dimensions": 512,
"date": "2025-08-01T21:59:56.632Z",
"source": "tensorflow-models/universal-sentence-encoder",
"savedLocally": true,
"savedWith": "manual-embedding",
"embeddingSize": 512,
"approach": "tfhub-reference"
}